text:
= {The paper empirically identifies the world's cultural zones, comprised of the countries with the distinctive patterns of values, and determines their relationship with the country's communist past and current state of democracy. The analysis is based on the countries' average values on the two main dimensions of cross-cultural variations: the traditional versus secular-rational and the survival versus self-expression values. The World Values Survey and European Values Study data from 101 countries were used. The K-means method of cluster analysis and the Variance Ration Criterion for determining the final number of clusters were performed. The solution with three clusters appeared as the most appropriate and theoretically meaningful, representing three broad cultural value syndromes. The first value syndrome was defined by low self-expression and high secular-rational values (the zone of secularized authority), the second one by low secular-rational and low self-expression values (the zone of traditional authority), while the third was characterized by high values on both value dimensions (the zone of emancipation). The countries' cluster membership is highly correlated with the (non-)communist past and the level of socioeconomic development. The countries in three cultural zones significantly differ in terms of the state of democracy: democracy is more fully developed in the countries in the cultural zone of emancipation, and the least developed in the countries with the prevailing traditional authority cultural outlook.},
  journal = {Quality \& Quantity},
  language = {en}
}

@article{pavoneUsingReferenceModels2020,
  title = {Using Reference Models in Variable Selection},
  author = {Pavone, Federico and Piironen, Juho and B{\"u}rkner, Paul-Christian and Vehtari, Aki},
  year = {2020},
  month = apr,
  abstract = {Variable selection, or more generally, model reduction is an important aspect of the statistical workflow aiming to provide insights from data. In this paper, we discuss and demonstrate the benefits of using a reference model in variable selection. A reference model acts as a noise-filter on the target variable by modeling its data generating mechanism. As a result, using the reference model predictions in the model selection procedure reduces the variability and improves stability leading to improved model selection performance. Assuming that a Bayesian reference model describes the true distribution of future data well, the theoretically preferred usage of the reference model is to project its predictive distribution to a reduced model leading to projection predictive variable selection approach. Alternatively, reference models may also be used in an ad-hoc manner in combination with common variable selection methods. In several numerical experiments, we investigate the performance of the projective prediction approach as well as alternative variable selection methods with and without reference models. Our results indicate that the use of reference models generally translates into better and more stable variable selection. Additionally, we demonstrate that the projection predictive approach shows superior performance as compared to alternative variable selection methods independently of whether or not they use reference models.},
  archivePrefix = {arXiv},
  eprint = {2004.13118},
  eprinttype = {arxiv},
  journal = {arXiv:2004.13118 [stat]},
  primaryClass = {stat}
}

@misc{PDFEnhancingAccelerating,
  title = {({{PDF}}) {{Enhancing}} and Accelerating Social Science via Automation: {{Challenges}} and Opportunities},
  shorttitle = {({{PDF}}) {{Enhancing}} and Accelerating Social Science via Automation},
  abstract = {ResearchGate is a network dedicated to science and research. Connect, collaborate and discover scientific publications, jobs and conferences. All for free.},
  file = {/home/aleksandar/Zotero/storage/AMWMU2EL/330645355_Enhancing_and_accelerating_social_science_via_automation_Challenges_and_opportunities.html},
  howpublished = {https://www.researchgate.net/publication/330645355\_Enhancing\_and\_accelerating\_social\_science\_via\_automation\_Challenges\_and\_opportunities},
  journal = {ResearchGate},
  language = {en}
}

@book{pearlBookWhyNew2018,
  title = {The Book of Why: The New Science of Cause and Effect},
  shorttitle = {The Book of Why},
  author = {Pearl, Judea and Mackenzie, Dana},
  year = {2018},
  edition = {First edition},
  publisher = {{Basic Books}},
  address = {{New York}},
  abstract = {"Everyone has heard the claim, "Correlation does not imply causation." What might sound like a reasonable dictum metastasized in the twentieth century into one of science's biggest obstacles, as a legion of researchers became unwilling to make the claim that one thing could cause another. Even two decades ago, asking a statistician a question like "Was it the aspirin that stopped my headache?" would have been like asking if he believed in voodoo, or at best a topic for conversation at a cocktail party rather than a legitimate target of scientific inquiry. Scientists were allowed to posit only that the probability that one thing was associated with another. This all changed with Judea Pearl, whose work on causality was not just a victory for common sense, but a revolution in the study of the world"--},
  isbn = {978-0-465-09760-9},
  lccn = {Q175.32.C38 P43 2018}
}

@article{pedersenDynamicsEuropeanParty1979,
  title = {The Dynamics of {{European}} Party Systems: {{Changing}} Patterns of Electoral Volatility},
  shorttitle = {{{THE DYNAMICS OF EUROPEAN PARTY SYSTEMS}}},
  author = {Pedersen, Mogens N.},
  year = {1979},
  month = mar,
  volume = {7},
  pages = {1--26},
  issn = {0304-4130, 1475-6765},
  doi = {10.1111/j.1475-6765.1979.tb01267.x},
  journal = {European Journal of Political Research},
  language = {en},
  number = {1}
}

@article{pedersenTwoStrategiesBuilding,
  title = {Two Strategies for Building a Personal Vote: {{Personalized}} Representation in the {{UK}} and {{Denmark}}},
  author = {Pedersen, Helene Helboe and {vanHeerde-Hudson}, Jennifer},
  doi = {10.1016/j.electstud.2019.02.010},
  abstract = {{$<$}div{$><$}h2{$>$}Abstract{$<$}/h2{$><$}p{$>$}Across parliamentary democracies, elected representatives constitute the link between citizens and government. MPs can connect with voters via the party label, or through personalized forms of representation, which is seen to be increasing in importance. However, scholars disagree on what explains variation in MPs' use of personalized representation strategies. In this article, we argue that politicians use different strategies to personalize the link between themselves and citizens: a {$<$}em{$>$}constituency-oriented{$<$}/em{$>$} and a {$<$}em{$>$}person-oriented{$<$}/em{$>$} strategy. To test our argument, we develop a new and novel dataset with behavioral measures of personalized representation. Using a content analyses of 698 British and Danish MPs' personal websites, we demonstrate that the use of personalization strategies is conditional on the incentives MPs face in terms of electoral insecurity, candidate selection procedures, and the electoral context of the system. Our findings show that the level and type of personalized politics vary across political systems and may pose different types of challenges to party democracies.{$<$}/p{$><$}/div{$>$}},
  journal = {Electoral Studies}
}

@article{pedersenTwoStrategiesBuildinga,
  title = {Two Strategies for Building a Personal Vote: {{Personalized}} Representation in the {{UK}} and {{Denmark}}},
  author = {Pedersen, Helene Helboe and {vanHeerde-Hudson}, Jennifer},
  doi = {10.1016/j.electstud.2019.02.010},
  abstract = {{$<$}div{$><$}h2{$>$}Abstract{$<$}/h2{$><$}p{$>$}Across parliamentary democracies, elected representatives constitute the link between citizens and government. MPs can connect with voters via the party label, or through personalized forms of representation, which is seen to be increasing in importance. However, scholars disagree on what explains variation in MPs' use of personalized representation strategies. In this article, we argue that politicians use different strategies to personalize the link between themselves and citizens: a {$<$}em{$>$}constituency-oriented{$<$}/em{$>$} and a {$<$}em{$>$}person-oriented{$<$}/em{$>$} strategy. To test our argument, we develop a new and novel dataset with behavioral measures of personalized representation. Using a content analyses of 698 British and Danish MPs' personal websites, we demonstrate that the use of personalization strategies is conditional on the incentives MPs face in terms of electoral insecurity, candidate selection procedures, and the electoral context of the system. Our findings show that the level and type of personalized politics vary across political systems and may pose different types of challenges to party democracies.{$<$}/p{$><$}/div{$>$}},
  journal = {Electoral Studies}
}

@article{pedrazaNovelAnalyticalFormulation2020,
  title = {A Novel Analytical Formulation of the {{Axelrod}} Model},
  author = {Pedraza, Luc{\'i}a and Pinto, Sebasti{\'a}n and Pinasco, Juan Pablo and Balenzuela, Pablo},
  year = {2020},
  month = jun,
  abstract = {The Axelrod model of cultural dissemination has been widely studied in the field of statistical mechanics. The traditional version of this agent-based model is to assign a cultural vector of \$F\$ components to each agent, where each component can take one of \$Q\$ cultural trait. In this work, we introduce a novel set of mean field master equations to describe the model for \$F=2\$ and \$F=3\$ in complete graphs where all indirect interactions are explicitly calculated. We find that the transition between different macroscopic states is driven by initial conditions (set by parameter \$Q\$) and the size of the system \$N\$, who measures the balance between linear and cubic terms in master equations. We also find that this analytical approach fully agrees with simulations where the system does not break up during the dynamics and a scaling relation related to missing links reestablishes the agreement when this happens.},
  archivePrefix = {arXiv},
  eprint = {2006.15241},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Dropbox/Zotero/Pedraza et al/Pedraza et al_2020_A novel analytical formulation of the Axelrod model.pdf;/home/aleksandar/Zotero/storage/3U5Q26VI/2006.html},
  journal = {arXiv:2006.15241 [physics]},
  primaryClass = {physics}
}

@article{peelDetectabilityHierarchicalCommunities2020,
  title = {Detectability of Hierarchical Communities in Networks},
  author = {Peel, Leto and Schaub, Michael T.},
  year = {2020},
  month = sep,
  abstract = {We study the problem of recovering a planted hierarchy of partitions in a network. The detectability of a single planted partition has previously been analysed in detail and a phase transition has been identified below which the partition cannot be detected. Here we show that, in the hierarchical setting, there exist additional phases in which the presence of multiple consistent partitions can either help or hinder detection. Accordingly, the detectability limit for non-hierarchical partitions typically provides insufficient information about the detectability of the complete hierarchical structure, as we highlight with several constructive examples.},
  archivePrefix = {arXiv},
  eprint = {2009.07525},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Peel_Schaub/Peel_Schaub_2020_Detectability of hierarchical communities in networks.pdf;/home/aleksandar/Zotero/storage/LR8ADQ7B/2009.html},
  journal = {arXiv:2009.07525 [physics, stat]},
  primaryClass = {physics, stat}
}

@article{peetersRags2ridgesOneStopShopGraphical2020,
  title = {Rags2ridges: {{A One}}-{{Stop}}-{{Shop}} for {{Graphical Modeling}} of {{High}}-{{Dimensional Precision Matrices}}},
  shorttitle = {Rags2ridges},
  author = {Peeters, Carel F. W. and Bilgrau, Anders Ellern and {van Wieringen}, Wessel N.},
  year = {2020},
  month = oct,
  abstract = {A graphical model is an undirected network representing the conditional independence properties between random variables. Graphical modeling has become part and parcel of systems or network approaches to multivariate data, in particular when the variable dimension exceeds the observation dimension. rags2ridges is an R package for graphical modeling of high-dimensional precision matrices. It provides a modular framework for the extraction, visualization, and analysis of Gaussian graphical models from high-dimensional data. Moreover, it can handle the incorporation of prior information as well as multiple heterogeneous data classes. As such, it provides a one-stop-shop for graphical modeling of high-dimensional precision matrices. The functionality of the package is illustrated with an example dataset pertaining to blood-based metabolite measurements in persons suffering from Alzheimer's Disease.},
  archivePrefix = {arXiv},
  eprint = {2010.05619},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Peeters et al/Peeters et al_2020_rags2ridges.pdf;/home/aleksandar/Zotero/storage/PJAMP2CQ/2010.html},
  journal = {arXiv:2010.05619 [stat]},
  primaryClass = {stat}
}

@inproceedings{peiNonnegativeResidualMatrix2020,
  title = {Nonnegative {{Residual Matrix Factorization}} for {{Community Detection}}},
  booktitle = {Web {{Information Systems Engineering}} \textendash{} {{WISE}} 2020},
  author = {Pei, Yulong and Liu, Cong and Zheng, Chuanyang and Cheng, Long},
  editor = {Huang, Zhisheng and Beek, Wouter and Wang, Hua and Zhou, Rui and Zhang, Yanchun},
  year = {2020},
  pages = {196--209},
  publisher = {{Springer International Publishing}},
  address = {{Cham}},
  doi = {10.1007/978-3-030-62005-9_15},
  abstract = {Community detection is one of the most important and challenging problems in graph mining and social network analysis. Nonnegative Matrix Factorization (NMF) based methods have been proved to be effective in the task of community detection. However, real-world networks could be noisy and existing NMF based community detection methods are sensitive to the outliers and noise due to the utilization of the squared loss function to measure the quality of graph regularization and network reconstruction. In this paper, we propose a framework based on the nonnegative residual matrix factorization (NRMF) to overcome this limitation. In this method, a residual matrix, represented by the matrix reconstruction error, is explicitly introduced to capture the impact of outliers and noise. The residual matrix should be sparse intuitively so some sparse regularization can be used to model the sparsity. Specifically, three different types of sparse regularization, i.e., L0L0L\_0, L1L1L\_\{1\} and L2,1L2,1L\_\{2,1\}, have been studied. Multiplicative update rules and different thresholding operators are used to learn these lower-rank matrices. Extensive experiments on benchmark networks with and without known communities demonstrate that our framework is more robust so that it outperforms state-of-the-art NMF based approaches in community detection task.},
  isbn = {978-3-030-62005-9},
  language = {en},
  series = {Lecture {{Notes}} in {{Computer Science}}}
}

@article{penalozaMechanicsTreatmenteffectEstimate2019,
  title = {The {{Mechanics}} of {{Treatment}}-Effect {{Estimate Bias}} for {{Nonexperimental Data}}},
  author = {Penaloza, Roberto V. and Berends, Mark},
  year = {2019},
  month = jun,
  pages = {0049124119852375},
  issn = {0049-1241},
  doi = {10.1177/0049124119852375},
  abstract = {To measure ``treatment'' effects, social science researchers typically rely on nonexperimental data. In education, school and teacher effects on students are often measured through value-added models (VAMs) that are not fully understood. We propose a framework that relates to the education production function in its most flexible form and connects with the basic VAMs without using untenable assumptions. We illustrate how, due to measurement error (ME), cross-group imbalances created by nonrandom group assignment cause correlations that drive the models' treatment-effect estimate bias. We derive formulas to calculate bias and rank the models and show that no model is better in all situations. The framework and formulas' workings are verified and illustrated via simulation. We also evaluate the performance of latent variable/errors-in-variables models that handle ME and study the role of extra covariates including lags of the outcome.},
  journal = {Sociological Methods \& Research},
  language = {en}
}

@article{pereiraEfficientSimulationGaussian,
  title = {Efficient Simulation of {{Gaussian Markov}} Random Fields by {{Chebyshev}} Polynomial Approximation},
  author = {Pereira, Mike and Desassis, Nicolas},
  doi = {10.1016/j.spasta.2019.100359},
  abstract = {{$<$}p{$>$}This paper presents an algorithm to simulate Gaussian random vectors whose precision matrix can be expressed as a polynomial of a sparse matrix. This situation arises in particular when simulating Gaussian Markov random fields obtained by the finite elements discretization of the solutions of some stochastic partial derivative equations. The proposed algorithm uses a Chebyshev polynomial approximation to compute simulated vectors with a linear complexity. This method is asymptotically exact as the approximation order grows. Criteria based on tests of the statistical properties of the produced vectors are derived to determine minimal orders of approximation.{$<$}/p{$>$}},
  journal = {Spatial Statistics}
}

@article{pereiraEfficientSimulationGaussiana,
  title = {Efficient Simulation of {{Gaussian Markov}} Random Fields by {{Chebyshev}} Polynomial Approximation},
  author = {Pereira, Mike and Desassis, Nicolas},
  doi = {10.1016/j.spasta.2019.100359},
  abstract = {{$<$}p{$>$}This paper presents an algorithm to simulate Gaussian random vectors whose precision matrix can be expressed as a polynomial of a sparse matrix. This situation arises in particular when simulating Gaussian Markov random fields obtained by the finite elements discretization of the solutions of some stochastic partial derivative equations. The proposed algorithm uses a Chebyshev polynomial approximation to compute simulated vectors with a linear complexity. This method is asymptotically exact as the approximation order grows. Criteria based on tests of the statistical properties of the produced vectors are derived to determine minimal orders of approximation.{$<$}/p{$>$}},
  journal = {Spatial Statistics}
}

@article{perezyperezMethodologyFieldWork2020,
  title = {Towards a {{Methodology}} for {{Field Work}} in {{Computational Creativity}}},
  author = {{P{\'e}rez y P{\'e}rez}, Rafael and Ackerman, Margareta},
  year = {2020},
  month = sep,
  issn = {1882-7055},
  doi = {10.1007/s00354-020-00105-z},
  abstract = {This work proposes a methodology for conducting field work in computational creativity, referring to field work as the effort of actively making a system or its artifacts widely accessible outside the academic world. Field work aims to study how creative computer agents and/or their products influence society, and how the dynamics that arise from the interaction between people and those inventive machines or their artifacts can inform the design of computational creativity methods, systems and artefacts. In this paper, we reflect on our experiences making our systems ALYSIA and MEXICA broadly available. In the case of ALYSIA, the system itself was made accessible, whereas MEXICA's artifacts (stories) were shared through a traditionally published book for a broad readership. We then propose a five step methodology for effectively conducting field work in Computational Creativity. The participation of the computational creativity community is essential to test and enrich this methodology.},
  journal = {New Generation Computing},
  language = {en}
}

@article{perottiGeneralizationInformationTheory2020,
  title = {Towards a Generalization of Information Theory for Hierarchical Partitions},
  author = {Perotti, Juan Ignacio and Almeira, Nahuel and Saracco, Fabio},
  year = {2020},
  month = jun,
  volume = {101},
  pages = {062148},
  publisher = {{American Physical Society}},
  doi = {10.1103/PhysRevE.101.062148},
  abstract = {Complex systems often exhibit multiple levels of organization covering a wide range of physical scales, so the study of the hierarchical decomposition of their structure and function is frequently convenient. To better understand this phenomenon, we introduce a generalization of information theory that works with hierarchical partitions. We begin revisiting the recently introduced hierarchical mutual information (HMI), and show that it can be written as a level by level summation of classical conditional mutual information terms. Then, we prove that the HMI is bounded from above by the corresponding hierarchical joint entropy. In this way, in analogy to the classical case, we derive hierarchical generalizations of many other classical information-theoretic quantities. In particular, we prove that, as opposed to its classical counterpart, the hierarchical generalization of the variation of information is not a metric distance, but it admits a transformation into one. Moreover, focusing on potential applications of the existing developments of the theory, we show how to adjust by chance the HMI. We also corroborate and analyze all the presented theoretical results with exhaustive numerical computations, and include an illustrative application example of the introduced formalism. Finally, we mention some open problems that should be eventually addressed for the proposed generalization of information theory to reach maturity.},
  file = {/home/aleksandar/Zotero/storage/DVUN7CNC/PhysRevE.101.html},
  journal = {Physical Review E},
  keywords = {TODO},
  number = {6}
}

@article{pescetelliEffectsRecursiveCommunication,
  title = {The {{Effects}} of {{Recursive Communication Dynamics}} on {{Belief Updating}}},
  author = {Pescetelli, Niccolo and Yeung, Nick},
  pages = {50},
  abstract = {Many social interactions are characterised by dynamic interplay, such that individuals exert reciprocal influence over each other's behaviours and beliefs. The present study investigated how the dynamics of reciprocal influence affect individual beliefs in a social context, over and above the information communicated in an interaction. To this end, we developed a simple social decisionmaking paradigm in which two people are asked to make perceptual judgments while receiving information about each other's decisions. In a Static condition, information about the partner only conveyed their initial, independent judgment. However, in a Dynamic condition, each individual saw the evolving belief of their partner as they learnt about and responded to the individual's own judgment. The results indicated that in both conditions, the majority of confidence adjustments were characterised by an abrupt change followed by smaller adjustments around an equilibrium, and that participants' confidence was used to arbitrate conflict (although deviating from Bayesian norm). Crucially, recursive interaction had systematic effects on belief change relative to the Static baseline, magnifying confidence change when partners agreed and reducing confidence change when they disagreed. These findings indicate that during dynamic interactions\textemdash often a characteristic of real-life and online social contexts\textemdash information is collectively transformed rather than acted upon by individuals in isolation. Consequently, the output of social events is not only influenced by what the dyad knows but also by predictable recursive and self-reinforcing dynamics.},
  language = {en}
}

@article{pesicPersistenceTraditionalistValue2006,
  title = {Persistence of Traditionalist Value Orientations in {{Serbia}}},
  author = {Pe{\v s}i{\'c}, Jelena},
  year = {2006},
  volume = {48},
  pages = {289--307},
  issn = {0038-0318},
  doi = {10.2298/SOC0604289P},
  abstract = {Systematic failures in attempts to modernize Serbian society during the past two centuries have led to the survival of traditionalist value orientations. The long period of Ottoman rule allowed patriarchal, warrior-tribal cultural patterns to persist and shape the basis for national and overall cultural identity. Extreme poverty, autarkical agricultural production, the slow penetration of capitalism and a market economy, an undifferentiated social structure with majority of rural population, patriarchal organization of both the private and public sphere and the authoritarian character of authority, were characteristics of Serbian pre-modern society, which inhibited its development and contributed to the persistence of traditionalism. Although the socialist period was modernizing in many respects, homology between socialist and pre-modern collectivist, egalitarian and authoritarian orientation, made it easy for nationalism to penetrate and consequently led to decomposition of the state in civil wars. Delayed post-socialist transformation, characterized by civil war, economic collapse, extreme impoverishment, and international isolation, has only strengthened the orientation towards pre-modern patterns of identification. This paper examines the persistence of collectivism, authoritarianism and patriarchal orientation in the period of unhindered post-socialist transformation, based on the data obtained in the "South-East European Social Survey Project" (SEESSP), conducted from December 2003 to January 2004. These results are compared with those obtained in the research project "Changes in the Class Structure and Mobility in Serbia", conducted in 1989.},
  journal = {Sociologija},
  number = {4},
  pmid = {0038-03180604289P}
}

@article{peskowitzPolarizationDynamicsElectoralundefined/ed,
  title = {The Polarization Dynamics of Electoral Reforms},
  author = {Peskowitz, Zachary and Szewczyk, James},
  year = {undefined/ed},
  pages = {1--20},
  publisher = {{Cambridge University Press}},
  issn = {2049-8470, 2049-8489},
  doi = {10.1017/psrm.2020.14},
  abstract = {Electoral reforms affect legislative outcomes by influencing incumbent legislators' behavior, new entrants' behavior, and the probability that incumbents are replaced with new entrants. Empirical work on electoral reforms and polarization has focused on new entrants' behavior. We employ a simple decision theoretic framework with partial incumbent policy persistence and spatial voting to examine the three channels jointly. We show that a reform designed to encourage ideological moderation produces larger effects on polarization when the reform is implemented than when it is removed. The key insight is that implementing a moderation-inducing reform generates a set of challengers who are more likely to defeat incumbents while the incumbents are more likely to win reelection when the reform is removed. We then empirically examine how elections and legislative polarization respond to unlimited PAC contributions in state legislatures. Examining incumbents' decisions to stand for reelection, the electoral performance of incumbents who do run, and partisan polarization, we find empirical support for our predictions.},
  journal = {Political Science Research and Methods},
  language = {en}
}

@article{petersonBayesianModelingMultiple,
  title = {Bayesian {{Modeling}} of {{Multiple Structural Connectivity Networks During}} the {{Progression}} of {{Alzheimer}}'s {{Disease}}. ({{arXiv}}:1908.10965v2 [Stat.{{ME}}] {{UPDATED}})},
  author = {Peterson, Christine B. and Osborne, Nathan and Stingo, Francesco C. and Bourgeat, Pierrick and Doecke, James D. and Vannucci, Marina},
  doi = {arXiv:1908.10965v2},
  abstract = {Alzheimer's disease is the most common neurodegenerative disease. The aim of this study is to infer structural changes in brain connectivity resulting from disease progression using cortical thickness measurements from a cohort of participants who were either healthy control, or with mild cognitive impairment, or Alzheimer's disease patients. For this purpose, we develop a novel approach for inference of multiple networks with related edge values across groups. Specifically, we infer a Gaussian graphical model for each group within a joint framework, where we rely on Bayesian hierarchical priors to link the precision matrix entries across groups. Our proposal differs from existing approaches in that it flexibly learns which groups have the most similar edge values, and accounts for the strength of connection (rather than only edge presence or absence) when sharing information across groups. Our results identify key alterations in structural connectivity which may reflect disruptions to the healthy brain, such as decreased connectivity within the occipital lobe with increasing disease severity. We also illustrate the proposed method through simulations, where we demonstrate its performance in structure learning and precision matrix estimation with respect to alternative approaches.},
  journal = {arXiv Methodology}
}

@article{petersonBayesianModelingMultiplea,
  title = {Bayesian {{Modeling}} of {{Multiple Structural Connectivity Networks During}} the {{Progression}} of {{Alzheimer}}'s {{Disease}}. ({{arXiv}}:1908.10965v2 [Stat.{{ME}}] {{UPDATED}})},
  author = {Peterson, Christine B. and Osborne, Nathan and Stingo, Francesco C. and Bourgeat, Pierrick and Doecke, James D. and Vannucci, Marina},
  doi = {arXiv:1908.10965v2},
  abstract = {Alzheimer's disease is the most common neurodegenerative disease. The aim of this study is to infer structural changes in brain connectivity resulting from disease progression using cortical thickness measurements from a cohort of participants who were either healthy control, or with mild cognitive impairment, or Alzheimer's disease patients. For this purpose, we develop a novel approach for inference of multiple networks with related edge values across groups. Specifically, we infer a Gaussian graphical model for each group within a joint framework, where we rely on Bayesian hierarchical priors to link the precision matrix entries across groups. Our proposal differs from existing approaches in that it flexibly learns which groups have the most similar edge values, and accounts for the strength of connection (rather than only edge presence or absence) when sharing information across groups. Our results identify key alterations in structural connectivity which may reflect disruptions to the healthy brain, such as decreased connectivity within the occipital lobe with increasing disease severity. We also illustrate the proposed method through simulations, where we demonstrate its performance in structure learning and precision matrix estimation with respect to alternative approaches.},
  journal = {arXiv Methodology}
}

@article{petersonBayesianModelingMultipleb,
  title = {Bayesian {{Modeling}} of {{Multiple Structural Connectivity Networks During}} the {{Progression}} of {{Alzheimer}}'s {{Disease}}. ({{arXiv}}:1908.10965v2 [Stat.{{ME}}] {{UPDATED}})},
  author = {Peterson, Christine B. and Osborne, Nathan and Stingo, Francesco C. and Bourgeat, Pierrick and Doecke, James D. and Vannucci, Marina},
  doi = {arXiv:1908.10965v2},
  abstract = {Alzheimer's disease is the most common neurodegenerative disease. The aim of this study is to infer structural changes in brain connectivity resulting from disease progression using cortical thickness measurements from a cohort of participants who were either healthy control, or with mild cognitive impairment, or Alzheimer's disease patients. For this purpose, we develop a novel approach for inference of multiple networks with related edge values across groups. Specifically, we infer a Gaussian graphical model for each group within a joint framework, where we rely on Bayesian hierarchical priors to link the precision matrix entries across groups. Our proposal differs from existing approaches in that it flexibly learns which groups have the most similar edge values, and accounts for the strength of connection (rather than only edge presence or absence) when sharing information across groups. Our results identify key alterations in structural connectivity which may reflect disruptions to the healthy brain, such as decreased connectivity within the occipital lobe with increasing disease severity. We also illustrate the proposed method through simulations, where we demonstrate its performance in structure learning and precision matrix estimation with respect to alternative approaches.},
  journal = {arXiv Methodology}
}

@article{petrakisObjectiveBayesStructure,
  title = {Objective {{Bayes Structure Learning}} in {{Gaussian Graphical Models}}},
  author = {Petrakis, Nikolaos},
  pages = {116},
  language = {en}
}

@article{petrakisObjectiveMethodsGraphical,
  title = {Objective Methods for Graphical Structural Learning},
  author = {Petrakis, Nikolaos and Peluso, Stefano and Fouskakis, Dimitris and Consonni, Guido},
  volume = {n/a},
  issn = {1467-9574},
  doi = {10.1111/stan.12211},
  abstract = {Graphical models are used for expressing conditional independence relationships among variables by the means of graphs, whose structure is typically unknown and must be inferred by the data at hand. We propose a theoretically sound Objective Bayes procedure for graphical model selection. Our method is based on the Expected-Posterior Prior and on the Power-Expected-Posterior Prior. We use as input of the proposed methodology a default improper prior and suggest computationally efficient approximations of Bayes factors and posterior odds. In a variety of simulated scenarios with varying number of nodes and sample sizes, we show that our method is highly competitive with, or better than, current benchmarks. We also discuss an application to protein-signaling data, which wieldy confirms existing results in the scientific literature.},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/stan.12211},
  copyright = {\textcopyright{} 2020 The Authors. Statistica Neerlandica \textcopyright{} 2020 VVS},
  file = {/home/aleksandar/Dropbox/Zotero/Petrakis et al/Petrakis et al_Objective methods for graphical structural learning.pdf},
  journal = {Statistica Neerlandica},
  language = {en},
  number = {n/a}
}

@article{petricevicWhyCitizensNot2019,
  title = {Why {{Do Citizens Not Turn Out}}? {{The Effect}} of {{Election}}-{{Specific Knowledge}} on {{Turnout}} in {{European Elections}} in {{Eastern Europe}}},
  shorttitle = {Why {{Do Citizens Not Turn Out}}?},
  author = {Petri{\v c}evi{\'c}, Vanja and Stockemer, Daniel},
  year = {2019},
  month = oct,
  pages = {0888325419870228},
  issn = {0888-3254},
  doi = {10.1177/0888325419870228},
  abstract = {Throughout the European Parliament's nearly forty years of existence, electoral turnout in European parliamentary elections has consistently been lower than electoral turnout in the national elections of the member states. This is particularly the case for the majority of states in Eastern Europe where turnout in European Elections has resulted in low electoral participation of eligible voters. Focusing on the 2014 election to the European Parliament, we highlight that low election-specific knowledge contributes to these low participation rates. In more detail, we rely on name recognition of the main candidates of the three main party groups, and show that knowledge of these candidates is more than twice as high in Western Europe as in Eastern Europe. Second, we illustrate that these low knowledge levels in the East also help explain the larger turnout gap between national and European elections in the East.},
  journal = {East European Politics and Societies},
  language = {en}
}

@article{petrovicChangesMaritalBehavior2011,
  title = {Changes of Marital Behavior and Family Patterns in Post-Socialist Countries: {{Delayed}}, Incomplete or Specific Second Demographic Transition?},
  shorttitle = {Changes of Marital Behavior and Family Patterns in Post-Socialist Countries},
  author = {Petrovi{\'c}, Mina},
  year = {2011},
  volume = {49},
  pages = {53--78},
  issn = {0038-982X, 2217-3986},
  doi = {10.2298/STNV1101053P},
  journal = {Stanovnistvo},
  language = {en},
  number = {1}
}

@article{piercePolarizationCorrectVoting2019,
  ids = {piercePolarizationCorrectVoting,piercePolarizationCorrectVotinga},
  title = {Polarization and Correct Voting in {{U}}.{{S}}. Presidential Elections},
  author = {Pierce, Douglas R. and Lau, Richard R.},
  year = {2019},
  month = aug,
  volume = {60},
  pages = {102048},
  issn = {02613794},
  doi = {10.1016/j.electstud.2019.102048},
  journal = {Electoral Studies},
  language = {en}
}

@article{pierreImpactInstitutionsSocial,
  title = {The {{Impact}} of {{Institutions}} on {{Social Polarization}}},
  author = {Pierre, Norbert},
  pages = {19},
  abstract = {Representing social institutions in terms of the well-known DeGroot model of information transmission and social learning, the paper shows the ability of institutions to facilitate or prevent social consensus. It is also shown that the disconnectedness of institutions from the social network has a profound impact on the time required to achieve consensus.},
  file = {/home/aleksandar/Dropbox/Zotero/Pierre/Pierre_The Impact of Institutions on Social Polarization.pdf},
  language = {en}
}

@misc{pigeeLessonsWeVe2019,
  title = {Lessons We've Learned about Writing the Empirical Journal Article},
  author = {{pigee}},
  year = {2019},
  month = oct,
  abstract = {How about a little blast from the past?~ In rooting around in an old hard drive searching for Pat Hill's original CV [1], I came across a document that we wrote way back in 2006 on how to write mor\ldots},
  journal = {pigee},
  language = {en}
}

@article{pinaudVisualizationTechniquesComparison2020,
  title = {On Visualization Techniques Comparison for Large Social Networks Overview: {{A}} User Experiment},
  shorttitle = {On Visualization Techniques Comparison for Large Social Networks Overview},
  author = {Pinaud, Bruno and Vallet, Jason and Melan{\c c}on, Guy},
  year = {2020},
  month = oct,
  issn = {2468-502X},
  doi = {10.1016/j.visinf.2020.09.005},
  abstract = {Visualizing social networks, especially an overview emphasizing their structure, i.e., communities and their interconnections, is known to be a challenging problem. In this paper, we present a set of design rationales to build such overview visualizations of social networks and our solution called Jasper. We evaluate its performances against two of the most wide-spread visualization techniques (matrix and node-link diagram) in a human\textendash computer controlled experiment based on community-related tasks. While none of the techniques emerge as the overwhelming winner, Jasper appears to be one of the best method for each task; a fact sustained by the marks given by the users. Overall, Jasper can be seen as an all-encompassing solution for quickly producing legible and compact overviews of large social networks on a single modern computer.},
  journal = {Visual Informatics},
  language = {en}
}

@article{pincusNonlinearDynamicalSystems2018,
  title = {Nonlinear {{Dynamical Systems}} and {{Humanistic Psychology}}},
  author = {Pincus, David and Kiefer, Adam W. and Beyer, Jessica I.},
  year = {2018},
  month = may,
  volume = {58},
  pages = {343--366},
  publisher = {{SAGE Publications Inc}},
  issn = {0022-1678},
  doi = {10.1177/0022167817741784},
  abstract = {The recent debunking by Brown, Sokal, and Friedman of some high-profile results applying chaos theory to positive psychology creates the opportunity to shed light on the quality work that has been done by others in this area. Too many humanists may be unaware of the large volume of legitimate work that exists in the literature apart from Fredrickson and Losada's article. Often, such legitimate lines of research are ignored, not for lack of scientific merit, but because of artificial guild boundaries and similar silos that separate groups of scientists\textemdash even when working in similar areas. It would be unfortunate to have one ``bad apple'' of an article spoil the reputation of the good scientific progress that has been made over the past couple of decades applying nonlinear dynamical systems theory to humanistic concepts. The present article is intended to help prevent and correct some of these problems, by providing an accesible review of some of this higher quality work.},
  file = {/home/aleksandar/Dropbox/Zotero/Pincus et al/Pincus et al_2018_Nonlinear Dynamical Systems and Humanistic Psychology.pdf},
  journal = {Journal of Humanistic Psychology},
  keywords = {nonlinear dynamics,positive psychology},
  language = {en},
  number = {3}
}

@article{pinillos-francoRelationshipSocialCapital2018,
  title = {The Relationship between Social Capital and Self-Rated Health: {{A}} Gendered Analysis of 17 {{European}} Countries},
  shorttitle = {The Relationship between Social Capital and Self-Rated Health},
  author = {{Pinillos-Franco}, Sara and Kawachi, Ichiro},
  year = {2018},
  month = dec,
  volume = {219},
  pages = {30--35},
  issn = {02779536},
  doi = {10.1016/j.socscimed.2018.10.010},
  journal = {Social Science \& Medicine},
  language = {en}
}

@article{pirroEdgeCentricNetworkEmbeddings2020,
  title = {Toward {{Edge}}-{{Centric Network Embeddings}}},
  author = {Pirr{\`o}, Giuseppe},
  year = {2020},
  month = nov,
  abstract = {Existing network embedding approaches tackle the problem of learning low-dimensional node representations. However, networks can also be seen in the light of edges interlinking pairs of nodes. The broad goal of this paper is to introduce edge-centric network embeddings. We present an approach called ECNE, which instead of computing node embeddings directly, computes edge embeddings by relying on the notion of line graph coupled with an edge weighting mechanism to preserve the dynamic of the original graph in the line graph. We also present a link prediction framework called ECNE-LP, which given a target link (\dbend\dbend\dbend\dbend\dbend\dbend, \dbend\dbend\dbend\dbend\dbend\dbend ) first collects paths between nodes \dbend\dbend\dbend\dbend\dbend\dbend{} and \dbend\dbend\dbend\dbend\dbend\dbend, then directly embeds the edges in these paths, and finally aggregates them toward predicting the existence of a link. We show that both ECNE and ECNE-LP bring benefit wrt the state-of-the-art.},
  archivePrefix = {arXiv},
  eprint = {2011.05650},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/DC8IKRM3/Pirrò - 2020 - Toward Edge-Centric Network Embeddings.pdf},
  journal = {arXiv:2011.05650 [cs]},
  keywords = {Computer Science - Machine Learning,Computer Science - Social and Information Networks},
  language = {en},
  primaryClass = {cs}
}

@article{pivaNetworksGrowthPreferential2020,
  title = {Networks with {{Growth}} and {{Preferential Attachment}}: {{Modeling}} and {{Applications}}},
  shorttitle = {Networks with {{Growth}} and {{Preferential Attachment}}},
  author = {Piva, Gabriel G. and Ribeiro, Fabiano L. and Mata, Angelica S.},
  year = {2020},
  month = jul,
  abstract = {In this article we presented a brief study of the main network models with growth and preferential attachment. Such models are interesting because they present several characteristics of real systems. We started with the classical model proposed by Barabasi and Albert: nodes are added to the network connecting preferably to other nodes that are more connected. We also presented models that consider more representative elements from social perspectives, such as the homophily between the vertices or the fitness that each node has to build connections. Furthermore, we showed a version of these models including the Euclidean distance between the nodes as a preferential attachment rule. Our objective is to investigate the basic properties of these networks as distribution of connectivity, degree correlation, shortest path, cluster coefficient and how these characteristics are affected by the preferential attachment rules. Finally, we also provided a comparison of these synthetic networks with real ones. We found that characteristics as homophily, fitness and geographic distance are significant preferential attachment rules to modeling real networks. These rules can change the degree distribution form of these synthetic network models and make them more suitable to model real networks.},
  archivePrefix = {arXiv},
  eprint = {2007.01349},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Dropbox/Zotero/Piva et al/Piva et al_2020_Networks with Growth and Preferential Attachment.pdf;/home/aleksandar/Zotero/storage/G2T8ERCG/2007.html},
  journal = {arXiv:2007.01349 [physics]},
  primaryClass = {physics}
}

@article{plessNewCulturalCleavageundefined/ed,
  title = {The ``{{New}}'' {{Cultural Cleavage}} in {{Western Europe}}: {{A Coalescence}} of {{Religious}} and {{Secular Value Divides}}?},
  shorttitle = {The ``{{New}}'' {{Cultural Cleavage}} in {{Western Europe}}},
  author = {Pless, Anna and Tromp, Paul and Houtman, Dick},
  year = {undefined/ed},
  pages = {1--20},
  issn = {1755-0483, 1755-0491},
  doi = {10.1017/S175504831900049X},
  abstract = {Moral traditionalism versus progressiveness and secular authoritarianism versus libertarianism are often understood as central to the same ``new'' cultural cleavage in politics. Despite the often-found sizable correlations between these two cultural value divides, the present paper theorizes that this relationship is not a cross-contextual constant, but rather a specific feature of secularized contexts where moral traditionalism is relatively marginal. We test this theory by means of a two-stage statistical analysis of the data from the four waves of the European Values Study (1981\textendash 2008) for 17 Western European countries. Our findings confirm that the two value divides are most strongly connected in the most secularized contexts because the latter are least morally traditionalist. While the two cultural divides hence tend to be distinct in more religious Western-European countries, they tend to coalesce into one single ``new'' cultural divide in more secular ones.},
  file = {/home/aleksandar/Zotero/storage/PS9MXYG9/CB60094CF58D23F6C88EC29E9606B1A0.html},
  journal = {Politics and Religion},
  language = {en}
}

@article{plutzerBecomingHabitualVoter2002,
  title = {Becoming a {{Habitual Voter}}: {{Inertia}}, {{Resources}}, and {{Growth}} in {{Young Adulthood}}},
  shorttitle = {Becoming a {{Habitual Voter}}},
  author = {Plutzer, Eric},
  year = {2002},
  month = mar,
  volume = {96},
  pages = {41--56},
  publisher = {{Cambridge University Press}},
  issn = {1537-5943, 0003-0554},
  doi = {10.1017/S0003055402004227},
  abstract = {This paper reframes our inquiry into voter turnout by making aging the lens through which the traditional resource and cost measures of previous turnout research are viewed, thereby making three related contributions. (1) I offer a developmental theory of turnout. This framework follows from the observation that most citizens are habitual voters or habitual nonvoters (they display inertia). Most young citizens start their political lives as habitual nonvoters but they vary in how long it takes to develop into habitual voters. With this transition at the core of the framework, previous findings concerning costs and resources can easily be integrated into developmental theory. (2) I make a methodological contribution by applying latent growth curve models to panel data. (3) Finally, the empirical analyses provide the developmental theory with strong support and also provide a better understanding of the roles of aging, parenthood, partisanship, and geographic mobility.},
  file = {/home/aleksandar/Documents/Zotero/Plutzer/Plutzer_2002_Becoming a Habitual Voter2.pdf;/home/aleksandar/Zotero/storage/XK8IV22B/9EA1F561496D714346491B25B0D52239.html},
  journal = {American Political Science Review},
  language = {en},
  number = {1}
}

@article{polackoPolicyPolarizationIncome2020,
  title = {Policy {{Polarization}}, {{Income Inequality}} and {{Turnout}}},
  author = {Polacko, Matthew and Heath, Oliver and {Lewis-Beck}, Michael S and Dassonneville, Ruth},
  year = {2020},
  month = apr,
  pages = {0032321720906581},
  publisher = {{SAGE Publications Ltd}},
  issn = {0032-3217},
  doi = {10.1177/0032321720906581},
  abstract = {Past research on the relationship between income inequality and turnout has produced mixed results, with some studies suggesting that income inequality leads to lower turnout while other studies find little or no significant effects. In this article, we investigate the extent to which these mixed results are due to the contingent nature of inequality on turnout, which depends upon the nature of the policy options that are presented to the electorate. We test these expectations on data from national elections in 30 established democracies from 1965 through 2017 covering 300 elections. Regression analysis using country-level fixed effects reveals consistent evidence in favor of our hypotheses: Inequality tends to have a negative impact on turnout, especially in depolarized party systems, but as party system polarization increases the negative impact of inequality is mitigated.},
  journal = {Political Studies},
  language = {en}
}

@misc{PolicyPolarizationIncome,
  title = {Policy {{Polarization}}, {{Income Inequality}} and {{Turnout}} - {{Matthew Polacko}}, {{Oliver Heath}}, {{Michael S Lewis}}-{{Beck}}, {{Ruth Dassonneville}},},
  howpublished = {https://journals.sagepub.com/doi/abs/10.1177/0032321720906581}
}

@article{politiMoreRoyalistKing,
  title = {More {{Royalist Than}} the {{King}}? {{Immigration Policy Attitudes Among Naturalized Citizens}}},
  shorttitle = {More {{Royalist Than}} the {{King}}?},
  author = {Politi, Emanuele and Chipeaux, Marion and Lorenzi-Cioldi, Fabio and Staerkl{\'e}, Christian},
  volume = {n/a},
  issn = {1467-9221},
  doi = {10.1111/pops.12642},
  abstract = {Social psychological research has analyzed immigration attitudes mostly from the perspective of natives without an immigrant background. Nevertheless, an increasing number of migrants obtain national citizenship and take a stance towards immigration policies. By studying immigration policy attitudes reported by naturalized citizens, this article develops a dual-pathway model of immigrant political incorporation featuring pathways of either absorption or transformation. Based on a unique sample of immigrants who just accomplished the naturalization procedure (N = 566), we investigate participants' preferences for permissive or restrictive immigration policies as a function of their naturalization motives and expectations about how immigrants should acculturate in the receiving society (i.e., acculturation orientations). Our findings provide evidence for both processes of political absorption and transformation. On the one hand, belongingness motives underlying naturalization were connected to orientations towards host culture adoption, which in turn predicted support for restrictive immigration policies. On the other hand, instrumental motives were connected to orientations towards heritage culture maintenance, which in turn predicted support for permissive immigration policies. To conclude, we discuss the social psychological dynamics involved in the transition from national outsiders to national insiders and highlight the effects of naturalization on power relations between national majority and immigrant minority groups.},
  copyright = {\textcopyright{} 2020 International Society of Political Psychology},
  file = {/home/aleksandar/Zotero/storage/S6FUNXUD/pops.html},
  journal = {Political Psychology},
  language = {en},
  number = {n/a}
}

@article{ponsComputingCommunitiesLarge2005,
  title = {Computing Communities in Large Networks Using Random Walks (Long Version)},
  author = {Pons, Pascal and Latapy, Matthieu},
  year = {2005},
  month = dec,
  abstract = {Dense subgraphs of sparse graphs (communities), which appear in most real-world complex networks, play an important role in many contexts. Computing them however is generally expensive. We propose here a measure of similarities between vertices based on random walks which has several important advantages: it captures well the community structure in a network, it can be computed efficiently, and it can be used in an agglomerative algorithm to compute efficiently the community structure of a network. We propose such an algorithm, called Walktrap, which runs in time O(mn\^2) and space O(n\^2) in the worst case, and in time O(n\^2log n) and space O(n\^2) in most real-world cases (n and m are respectively the number of vertices and edges in the input graph). Extensive comparison tests show that our algorithm surpasses previously proposed ones concerning the quality of the obtained community structures and that it stands among the best ones concerning the running time.},
  archivePrefix = {arXiv},
  eprint = {physics/0512106},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/UVGA5DPC/0512106.html},
  journal = {arXiv:physics/0512106}
}

@inproceedings{ponsComputingCommunitiesLarge2005a,
  title = {Computing Communities in Large Networks Using Random Walks},
  booktitle = {Computer and {{Information Sciences}} - {{ISCIS}} 2005},
  author = {Pons, Pascal and Latapy, Matthieu},
  editor = {Yolum, Pinar and G{\"u}ng{\"o}r, Tunga and G{\"u}rgen, Fikret and {\"O}zturan, Can},
  year = {2005},
  pages = {284--293},
  publisher = {{Springer Berlin Heidelberg}},
  abstract = {Dense subgraphs of sparse graphs (communities), which appear in most real-world complex networks, play an important role in many contexts. Computing them however is generally expensive. We propose here a measure of similarities between vertices based on random walks which has several important advantages: it captures well the community structure in a network, it can be computed efficiently, it works at various scales, and it can be used in an agglomerative algorithm to compute efficiently the community structure of a network. We propose such an algorithm which runs in time O(mn                        2) and space O(n                        2) in the worst case, and in time O(n                        2log n) and space O(n                        2) in most real-world cases (n and m are respectively the number of vertices and edges in the input graph).},
  isbn = {978-3-540-32085-2}
}

@article{poole-wilsonEffectPHIonic1975,
  title = {Effect of {{pH}} on Ionic Exchange and Function in Rat and Rabbit Myocardium},
  author = {{Poole-Wilson}, P. A. and Langer, G. A.},
  year = {1975},
  month = sep,
  volume = {229},
  pages = {570--581},
  issn = {0002-9513},
  doi = {10.1152/ajplegacy.1975.229.3.570},
  abstract = {The effects of pH variation on ionic exchange and mechanical function were studied in the arterially perfused rat and rabbit septa. The pH and PCO2 of the control perfusate were 7.40 and 39 mmHg, respectively. In the rabbit septum a metabolic acidosis (pH equals 6.82, PCO2 equals 39 mmHg) caused a loss of 16\% of control tension in 12 min. Na+ and K+ exchange were unaltered. A comparable respiratory acidosis (pH equals 6.81, PCO2 equals 159 mmHg) caused a 51\% loss of tension in 2 min. Na+ exchange was unaltered but K+ efflux fell from 8.9 +/- 0.6 (mean +/- SE) to 4.9 +/- 0.3 mmol/kg dry wt per min (P less than 0.001, n equals 10). A net gain of K+ of 16.9 +/- 1.7 (n equals 14) mmol/kg dry wt occurred and was attributable to a delayed fall in K+ influx relative to efflux over 15 min. The net gain could not be mimicked by epinephrine administration or blocked by propranolol and was absent in the beating rat septum and the quiescent rabbit septum. These results suggest that the net uptake of K+, which appears to be dependent on a period of depolarization, and the changes of contractility are controlled by the H+ ion concentration at a cellular site whose exchange with the extracellular space is characterized by a considerable restriction of diffusion. Changes of contractility are not related to the net uptake of K+.},
  journal = {The American Journal of Physiology},
  language = {eng},
  number = {3},
  pmid = {2014}
}

@article{poorOpenSourceInspirationsComputational2020,
  title = {Open-{{Source}}'s {{Inspirations}} for {{Computational Social Science}}: {{Lessons}} from a {{Failed Analysis}}},
  shorttitle = {Open-{{Source}}'s {{Inspirations}} for {{Computational Social Science}}},
  author = {Poor, Nathaniel},
  year = {2020},
  month = aug,
  volume = {8},
  pages = {231--238},
  issn = {2183-2439},
  doi = {10.17645/mac.v8i3.3163},
  abstract = {The questions we can ask currently, building on decades of research, call for advanced methods and understanding. We now have large, complex data sets that require more than complex statistical analysis to yield human answers. Yet as some researchers have pointed out, we also have challenges, especially in computational social science. In a recent project I faced several such challenges and eventually realized that the relevant issues were familiar to users of free and open-source software. I needed a team with diverse skills and knowledge to tackle methods, theories, and topics. We needed to iterate over the entire project: from the initial theories to the data to the methods to the results. We had to understand how to work when some data was freely available but other data that might benefit the research was not. More broadly, computational social scientists may need creative solutions to slippery problems, such as restrictions imposed by terms of service for sites from which we wish to gather data. Are these terms legal, are they enforced, or do our institutional review boards care? Lastly\textemdash perhaps most importantly and dauntingly\textemdash we may need to challenge laws relating to digital data and access, although so far this conflict has been rare. Can we succeed as open-source advocates have?},
  file = {/home/aleksandar/Zotero/storage/6YYIP3IY/Poor - 2020 - Open-Source’s Inspirations for Computational Socia.pdf},
  journal = {Media and Communication},
  language = {en},
  number = {3}
}

@article{popescuParliamentaryPresidentialElections2003,
  title = {The Parliamentary and Presidential Elections in {{Romania}}, {{November}} 2000},
  author = {Popescu, Marina},
  year = {2003},
  month = jun,
  volume = {22},
  pages = {325--335},
  issn = {02613794},
  doi = {10.1016/S0261-3794(02)00026-4},
  journal = {Electoral Studies},
  language = {en},
  number = {2}
}

@book{porterGeographicalSociologyTheoretical2012,
  title = {Geographical Sociology: {{Theoretical}} Foundations and Methodological Applications in the Sociology of Location},
  shorttitle = {Geographical Sociology},
  author = {Porter, Jeremy Reed and Howell, Frank Mobley},
  year = {2012},
  publisher = {{Springer}},
  address = {{Dordrecht}},
  annotation = {OCLC: 761857946},
  isbn = {978-94-007-3849-2 978-94-007-3848-5},
  language = {eng},
  number = {105},
  series = {The {{GeoJournal}} Library}
}

@article{possieriNewMetricUnderstanding2020,
  title = {A New Metric for Understanding Hidden Political Influences from Voting Records},
  author = {Possieri, Corrado and Ravazzi, Chiara and Dabbene, Fabrizio and Calafiore, Giuseppe C.},
  year = {2020},
  month = sep,
  volume = {15},
  pages = {e0238481},
  publisher = {{Public Library of Science}},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0238481},
  abstract = {Inspired by the increasing attention of the scientific community towards the understanding of human relationships and actions in social sciences, in this paper we address the problem of inferring from voting data the hidden influence on individuals from competing ideology groups. As a case study, we present an analysis of the closeness of members of the Italian Senate to political parties during the XVII Legislature. The proposed approach is aimed at automatic extraction of the relevant information by disentangling the actual influences from noise, via a two step procedure. First, a sparse principal component projection is performed on the standardized voting data. Then, the projected data is combined with a generative mixture model, and an information theoretic measure, which we refer to as Political Data-aNalytic Affinity (Political DNA), is finally derived. We show that the definition of this new affinity measure, together with suitable visualization tools for displaying the results of analysis, allows a better understanding and interpretability of the relationships among political groups.},
  file = {/home/aleksandar/Zotero/storage/TFAMHGV5/Possieri et al_2020_A new metric for understanding hidden political influences from voting records.pdf;/home/aleksandar/Zotero/storage/QTTFIP8V/article.html},
  journal = {PLOS ONE},
  language = {en},
  number = {9}
}

@inproceedings{powellNewApproachesElectoral2009,
  title = {New Approaches to Electoral Volatility: {{Evidence}} from Postcommunist Countries},
  booktitle = {{{APSA}} 2009 {{Toronto Meeting Paper}}},
  author = {Powell, Eleanor Neff and Tucker, Joshua A.},
  year = {2009},
  address = {{Toronto}}
}

@article{powellRevisitingElectoralVolatility2014,
  title = {Revisiting Electoral Volatility in Post-Communist Countries: {{New}} Data, New Results and New Approaches},
  shorttitle = {Revisiting {{Electoral Volatility}} in {{Post}}-{{Communist Countries}}},
  author = {Powell, E. N. and Tucker, Joshua A.},
  year = {2014},
  month = jan,
  volume = {44},
  pages = {123--147},
  issn = {0007-1234, 1469-2112},
  doi = {10.1017/S0007123412000531},
  journal = {British Journal of Political Science},
  language = {en},
  number = {1}
}

@article{powellRevisitingElectoralVolatilityJanuary,
  title = {Revisiting {{Electoral Volatility}} in \{\vphantom\}{{Post}}\vphantom\{\}-\{\vphantom\}{{Com}}},
  shorttitle = {Revisiting \{\vphantom\}{{Electoral}}\vphantom\{\} \{\vphantom\}{{Volatility}}\vphantom\{\} in \{\vphantom\}{{Post}}\vphantom\{\}-\{\vphantom\}{{Com}}},
  author = {Powell, Eleanor Neff and Tucker, Joshua A.},
  year = {January},
  pages = {123--147},
  issn = {00071234},
  abstract = {This article provides a detailed set of coding rules for disaggregating electoral volatility into two components: volatility caused by new party entry and old party exit, and volatility caused by vote switching across existing parties. After providing an overview of both types of volatility in post-communist countries, the causes of volatility are analysed using a larger dataset than those used in previous studies. The results are startling: most findings based on elections in post-communist countries included in previous studies disappear. Instead, entry and exit volatility is found to be largely a function of long-term economic recovery, and it becomes clear that very little is known about what causes `party switching' volatility. As a robustness test of this latter result, the authors demonstrate that systematic explanations for party-switching volatility in Western Europe can indeed be found. [ABSTRACT FROM PUBLISHER]},
  journal = {British Journal of Political Science},
  number = {1}
}

@misc{PrincipledBayesianWorkflow,
  title = {Towards {{A Principled Bayesian Workflow}}},
  file = {/home/aleksandar/Zotero/storage/DSQ5WBBN/principled_bayesian_workflow.html},
  howpublished = {https://betanalpha.github.io/assets/case\_studies/principled\_bayesian\_workflow.html}
}

@misc{ProbabilisticBuildingBlocks,
  title = {Probabilistic {{Building Blocks}}},
  file = {/home/aleksandar/Zotero/storage/PHRX8JMQ/probability_densities.html},
  howpublished = {https://betanalpha.github.io/assets/case\_studies/probability\_densities.html}
}

@misc{ProbabilisticComputation,
  title = {Probabilistic {{Computation}}},
  file = {/home/aleksandar/Zotero/storage/ZGDFSHSI/probabilistic_computation.html},
  howpublished = {https://betanalpha.github.io/assets/case\_studies/probabilistic\_computation.html}
}

@misc{ProbabilisticModelingStatistical,
  title = {Probabilistic {{Modeling}} and {{Statistical Inference}}},
  file = {/home/aleksandar/Zotero/storage/5EJZNDKF/modeling_and_inference.html},
  howpublished = {https://betanalpha.github.io/assets/case\_studies/modeling\_and\_inference.html}
}

@misc{ProbabilityTheoryScientists,
  title = {Probability {{Theory}} ({{For Scientists}} and {{Engineers}})},
  file = {/home/aleksandar/Zotero/storage/ZLXNTPCT/probability_theory.html},
  howpublished = {https://betanalpha.github.io/assets/case\_studies/probability\_theory.html}
}

@misc{ProductPlacement,
  title = {Product {{Placement}}},
  file = {/home/aleksandar/Zotero/storage/UJS9CF6L/probability_on_product_spaces.html},
  howpublished = {https://betanalpha.github.io/assets/case\_studies/probability\_on\_product\_spaces.html}
}

@article{prokhorenkovaUsingSyntheticNetworks2019,
  title = {Using Synthetic Networks for Parameter Tuning in Community Detection},
  author = {Prokhorenkova, Liudmila},
  year = {2019},
  month = jun,
  abstract = {Community detection is one of the most important and challenging problems in network analysis. However, real-world networks may have very different structural properties and communities of various nature. As a result, it is hard (or even impossible) to develop one algorithm suitable for all datasets. A standard machine learning tool is to consider a parametric algorithm and choose its parameters based on the dataset at hand. However, this approach is not applicable to community detection since usually no labeled data is available for such parameter tuning. In this paper, we propose a simple and effective procedure allowing to tune hyperparameters of any given community detection algorithm without requiring any labeled data. The core idea is to generate a synthetic network with properties similar to a given real-world one, but with known communities. It turns out that tuning parameters on such synthetic graph also improves the quality for a given real-world network. To illustrate the effectiveness of the proposed algorithm, we show significant improvements obtained for several well-known parametric community detection algorithms on a variety of synthetic and real-world datasets.},
  archivePrefix = {arXiv},
  eprint = {1906.04555},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/A83NJQZF/1906.html},
  journal = {arXiv:1906.04555 [physics]},
  primaryClass = {physics}
}

@misc{PsycNET,
  title = {{{PsycNET}}},
  file = {/home/aleksandar/Zotero/storage/YX962Y92/1988-01444-001.html},
  howpublished = {https://psycnet.apa.org/buy/1988-01444-001}
}

@article{PuttingPoliticsFirst,
  title = {Putting {{Politics First}}: {{The Impact}} of {{Politics}} on {{American Religious}} and {{Secular Orientations}}},
  doi = {10.1111/ajps.12365},
  abstract = {{$<$}div class="abstract-group"{$>$}    {$<$}section class="article-section article-section\_\_abstract" lang="en" data-lang="en" id="section-1-en"{$>$}       {$<$}h3 class="article-section\_\_header main abstractlang\_en main"{$>$}Abstract{$<$}/h3{$>$}       {$<$}div class="article-section\_\_content en main"{$>$}                              {$<$}p{$>$}Nearly all research on the political impact of Americans' religious and secular orientations             assumes that such orientations are exogenous to politics. Using multiwave panel and             experimental data, we find that religious and secular orientations are endogenous             to political orientations. In other words, religion and secularism are a consequence             as well as a cause of politics. In showing this, we make three major contributions.             First, we conceptualize and measure secular orientations in a new way\textemdash not just as             the absence of religion, but also as an affirmative secular identity and positive             commitment to secular principles. Second, our panel and experimental data allow for             the most definitive test to date of whether political orientations exert a causal             effect on religious and secular orientations. Third, we isolate the conditions under             which politics affects religious\textendash secular perspectives, thus identifying the mechanism             that underlies political orientations.          {$<$}/p{$>$}},
  journal = {American Journal of Political Science}
}

@article{PuttingPoliticsFirsta,
  title = {Putting {{Politics First}}: {{The Impact}} of {{Politics}} on {{American Religious}} and {{Secular Orientations}}},
  doi = {10.1111/ajps.12365},
  abstract = {{$<$}div class="abstract-group"{$>$}    {$<$}section class="article-section article-section\_\_abstract" lang="en" data-lang="en" id="section-1-en"{$>$}       {$<$}h3 class="article-section\_\_header main abstractlang\_en main"{$>$}Abstract{$<$}/h3{$>$}       {$<$}div class="article-section\_\_content en main"{$>$}                              {$<$}p{$>$}Nearly all research on the political impact of Americans' religious and secular orientations             assumes that such orientations are exogenous to politics. Using multiwave panel and             experimental data, we find that religious and secular orientations are endogenous             to political orientations. In other words, religion and secularism are a consequence             as well as a cause of politics. In showing this, we make three major contributions.             First, we conceptualize and measure secular orientations in a new way\textemdash not just as             the absence of religion, but also as an affirmative secular identity and positive             commitment to secular principles. Second, our panel and experimental data allow for             the most definitive test to date of whether political orientations exert a causal             effect on religious and secular orientations. Third, we isolate the conditions under             which politics affects religious\textendash secular perspectives, thus identifying the mechanism             that underlies political orientations.          {$<$}/p{$>$}},
  journal = {American Journal of Political Science}
}

@article{qiaoDetectingCommunitiesHeterogeneous2020,
  title = {Detecting {{Communities}} in {{Heterogeneous Multi}}-{{Relational Networks}}:{{A Message Passing}} Based {{Approach}}},
  shorttitle = {Detecting {{Communities}} in {{Heterogeneous Multi}}-{{Relational Networks}}},
  author = {Qiao, Maoying and Yu, Jun and Bian, Wei and Tao, Dacheng},
  year = {2020},
  month = apr,
  abstract = {Community is a common characteristic of networks including social networks, biological networks, computer and information networks, to name a few. Community detection is a basic step for exploring and analysing these network data. Typically, homogenous network is a type of networks which consists of only one type of objects with one type of links connecting them. There has been a large body of developments in models and algorithms to detect communities over it. However, real-world networks naturally exhibit heterogeneous qualities appearing as multiple types of objects with multi-relational links connecting them. Those heterogeneous information could facilitate the community detection for its constituent homogeneous networks, but has not been fully explored. In this paper, we exploit heterogeneous multi-relational networks (HMRNet) and propose an efficient message passing based algorithm to simultaneously detect communities for all homogeneous networks. Specifically, an HMRNet is reorganized into a hierarchical structure with homogeneous networks as its layers and heterogeneous links connecting them. To detect communities in such an HMRNet, the problem is formulated as a maximum a posterior (MAP) over a factor graph. Finally a message passing based algorithm is derived to find a best solution of the MAP problem. Evaluation on both synthetic and real-world networks confirms the effectiveness of the proposed method.},
  archivePrefix = {arXiv},
  eprint = {2004.02842},
  eprinttype = {arxiv},
  journal = {arXiv:2004.02842 [cs, stat]},
  primaryClass = {cs, stat}
}

@article{qiuLimitedIndividualAttention,
  title = {Limited Individual Attention and Online Virality of Low-Quality Information.},
  author = {Qiu, Xiaoyan and Oliveira, Diego F. M. and Shirazi, Alireza Sahami and Flammini, Alessandro and Menczer, Filippo},
  doi = {arXiv:1701.02694v3},
  abstract = {{$<$}p{$>$}Social media are massive marketplaces in which memes compete for our attention. We investigate the conditions in which the best ideas prevail in a stylized model of online social network, where agents have behavioral limitations in managing a heavy flow of information. We measure the relationship between the quality of an idea and its likelihood to become prevalent at the system level. We find that both information overload and limited attention contribute to a degradation in the market's discriminative power. A good tradeoff between discriminative power and diversity of information is possible according to the model. However, calibration with empirical data characterizing information load and finite attention in real social media reveals a weak correlation between quality and popularity of information. In these realistic conditions, the model predicts that low-quality information is just as likely to go viral, providing an interpretation for the high volume of misinformation we observe online. {$<$}/p{$>$}},
  journal = {arXiv Physics and Society}
}

@article{qiuLimitedIndividualAttentiona,
  title = {Limited Individual Attention and Online Virality of Low-Quality Information.},
  author = {Qiu, Xiaoyan and Oliveira, Diego F. M. and Shirazi, Alireza Sahami and Flammini, Alessandro and Menczer, Filippo},
  doi = {arXiv:1701.02694v3},
  abstract = {{$<$}p{$>$}Social media are massive marketplaces in which memes compete for our attention. We investigate the conditions in which the best ideas prevail in a stylized model of online social network, where agents have behavioral limitations in managing a heavy flow of information. We measure the relationship between the quality of an idea and its likelihood to become prevalent at the system level. We find that both information overload and limited attention contribute to a degradation in the market's discriminative power. A good tradeoff between discriminative power and diversity of information is possible according to the model. However, calibration with empirical data characterizing information load and finite attention in real social media reveals a weak correlation between quality and popularity of information. In these realistic conditions, the model predicts that low-quality information is just as likely to go viral, providing an interpretation for the high volume of misinformation we observe online. {$<$}/p{$>$}},
  journal = {arXiv Physics and Society}
}

@misc{QuantificationNetworkStructural,
  title = {Quantification of Network Structural Dissimilarities | {{Nature Communications}}},
  file = {/home/aleksandar/Documents/Zotero/undefined/Quantification of network structural dissimilarities Nature Communications.pdf;/home/aleksandar/Zotero/storage/4I4MHJW6/ncomms13928.html},
  howpublished = {https://www.nature.com/articles/ncomms13928\#MOESM614}
}

@article{quarantaHowCitizensEvaluate2018,
  title = {How Citizens Evaluate Democracy: An Assessment Using the {{European Social Survey}}},
  shorttitle = {How Citizens Evaluate Democracy},
  author = {Quaranta, Mario},
  year = {2018},
  month = may,
  volume = {10},
  pages = {191--217},
  issn = {1755-7739, 1755-7747},
  doi = {10.1017/S1755773917000054},
  abstract = {How do citizens evaluate democracy? Previous literature trying to address this question has often relied on single indicators to assess citizens' assessment of democracy. This article contributes to this debate by using multiple indicators measuring different attributes to find a summary measure of citizens' evaluations of democracy. Using the special module of the sixth round of the European Social Survey `Europeans' understandings and evaluations of democracy' and applying Bayesian factor analysis with country random effects, this article tests whether multiple indicators form an underlying trait measuring citizens' evaluations of democracy. It finds the scores of this measure at the individual and country levels and validates this measure against other measures built at the system level, including the `satisfaction with democracy' indicator, also illustrating its functioning as a dependent and an independent variable.},
  journal = {European Political Science Review},
  language = {en},
  number = {2}
}

@article{quarantaMeaningDemocracyCitizens2018,
  title = {The {{Meaning}} of {{Democracy}} to {{Citizens Across European Countries}} and the {{Factors Involved}}},
  author = {Quaranta, Mario},
  year = {2018},
  month = apr,
  volume = {136},
  pages = {859--880},
  issn = {0303-8300, 1573-0921},
  doi = {10.1007/s11205-016-1427-x},
  journal = {Social Indicators Research},
  language = {en},
  number = {3}
}

@article{quartagnoMultipleImputationSurvey,
  title = {Multiple {{Imputation}} with {{Survey Weights}}: {{A Multilevel Approach}}},
  shorttitle = {Multiple {{Imputation}} with {{Survey Weights}}},
  author = {Quartagno, M. and Carpenter, J. R. and Goldstein, H.},
  doi = {10.1093/jssam/smz036},
  abstract = {Abstract.  Multiple imputation is now well established as a practical and flexible method for analyzing partially observed data, particularly under the missing},
  file = {/home/aleksandar/Zotero/storage/3ZZKG3IJ/5569522.html},
  journal = {Journal of Survey Statistics and Methodology},
  language = {en}
}

@article{quattrociocchiOpinionDynamicsInteracting2014,
  title = {Opinion Dynamics on Interacting Networks: Media Competition and Social Influence},
  shorttitle = {Opinion Dynamics on Interacting Networks},
  author = {Quattrociocchi, Walter and Caldarelli, G. and Scala, A.},
  year = {2014},
  doi = {10.1038/srep04938},
  abstract = {The inner dynamics of the multiple actors of the informations systems \textendash{} i.e, T.V., newspapers, blogs, social network platforms, \textendash{} play a fundamental role on the evolution of the public opinion. Coherently with the recent history of the information system (from few main stream media to the massive diffusion of socio-technical system), in this work we investigate how main stream media signed interaction might shape the opinion space. In particular we focus on how different size (in the number of media) and interaction patterns of the information system may affect collective debates and thus the opinions' distribution. We introduce a sophisticated computational model of opinion dynamics which accounts for the coexistence of media and gossip as separated mechanisms and for their feedback loops. The model accounts also for the effect of the media communication patterns by considering both the simple case where each medium mimics the behavior of the most successful one (to maximize the audience) and the case where there is polarization and thus competition among media memes. We show that plurality and competition within information sources lead to stable configurations where several and distant cultures coexist.},
  file = {/home/aleksandar/Documents/Zotero/Quattrociocchi et al/Quattrociocchi et al_2014_Opinion dynamics on interacting networks.pdf},
  journal = {Scientific reports}
}

@article{quIdentifyingInfluentialSpreaders2020,
  title = {Identifying Influential Spreaders in Reversible Process},
  author = {Qu, Junyi and Tang, Ming and Liu, Ying and Guan, Shuguang},
  year = {2020},
  month = nov,
  volume = {140},
  pages = {110197},
  issn = {0960-0779},
  doi = {10.1016/j.chaos.2020.110197},
  abstract = {Identifying nodes with strong spreading capability is essential to control the spreading dynamics in many real-world scenarios, such as to direct the diffusion of public opinion, promote the adoption of new products and control the spreading of disease in social networks. Previous researches focused on the irreversible propagation process, such as the independent cascade model and the threshold model, which can be categorized into the Susceptible-Infected-Recovered (SIR) model type. The other type is the reversible propagation process with steady state such as the Susceptible-Infected-Susceptible (SIS) model, where the question of identifying important nodes has not received enough attention. In this paper, we study the problem of identifying vital nodes in the SIS spreading process in complex networks. We articulate a single-node control model to evaluate the influence of nodes in the reversible spreading system. By considering network structural and reversible spreading characteristics, we propose a new measure to quantify the node influence based on its neighbors' centrality and infection risk. By applying the commonly used centralities such as degree and coreness, this new measure can identify the most influential spreaders more accurately than the benchmark centralities. The proposed single-node control model and ranking method open up a new idea in identifying influential spreaders and validate the necessity of introducing the dynamical state in the reversible systems.},
  file = {/home/aleksandar/Zotero/storage/VCN4BRSS/S0960077920305932.html},
  journal = {Chaos, Solitons \& Fractals},
  language = {en}
}

@article{quinlanMisreportingTurnoutExplaining,
  title = {Misreporting {{Turnout}}: {{Explaining Survey Error}} in {{National Election Studies}}},
  author = {Quinlan, Stephen},
  pages = {22},
  abstract = {Election turnout is central to the health of a democracy, yet measuring it accurately in national election surveys presents major problems. Surveys consistently show that respondents overreport their turnout, usually by between 10 to 20 percentage points. To date, most research has been conducted on the United States, and what little comparative research exists has typically covered a small number of countries. In this paper we present the largest comparative study yet conducted on turnout misreporting. By utilising 20 years of data from Comparative Study of Electoral Systems (CSES) we analyse 184 elections across 55 different states. In addition to testing the social desirability and mode effects explanations for misreporting, we examine the electoral and party systems and survey methodology. The results show that the operation of the electoral system and the survey methodology are the most important explanations for misreporting, but there are also significant effects for the election context and the party system. These results provide an important corrective to current studies by showing that institutional factors are at least as important in shaping misreporting as methodology.},
  language = {en}
}

@article{quinnCausalDependenceTree2011,
  title = {Causal {{Dependence Tree Approximations}} of {{Joint Distributions}} for {{Multiple Random Processes}}},
  author = {Quinn, Christopher J. and Coleman, Todd P. and Kiyavash, Negar},
  year = {2011},
  month = jan,
  abstract = {We investigate approximating joint distributions of random processes with causal dependence tree distributions. Such distributions are particularly useful in providing parsimonious representation when there exists causal dynamics among processes. By extending the results by Chow and Liu on dependence tree approximations, we show that the best causal dependence tree approximation is the one which maximizes the sum of directed informations on its edges, where best is defined in terms of minimizing the KL-divergence between the original and the approximate distribution. Moreover, we describe a low-complexity algorithm to efficiently pick this approximate distribution.},
  archivePrefix = {arXiv},
  eprint = {1101.5108},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/8LREI8KF/1101.html},
  journal = {arXiv:1101.5108 [cs, math]},
  primaryClass = {cs, math}
}

@article{qureshiShortTitleSI,
  title = {Short {{Title}} ({{SI}}: {{Polarization}} and {{Social Media}})},
  author = {Qureshi, Israr and Bhatt, Babita and Gupta, Samrat and Tiwari, Amit Anand},
  pages = {11},
  language = {en}
}

@article{radhaInformationFlowPolitical2020,
  title = {Information Flow in Political Elections: A Stochastic Perspective},
  shorttitle = {Information Flow in Political Elections},
  author = {Radha, Santosh Kumar},
  year = {2020},
  month = sep,
  abstract = {Often times, a candidate's attractiveness is directly associated with his clear ideologies and opinions on various policies and social issues. Using the ideas of stochastic differential equations and Ornstein-Uhlenbeck Process, we develop a phenomenological model to understand the effect of (un)clearly communicating a candidate's stance on policies to the voting public. We will show that, counter intuitively, there are quantifiable advantages to be vague on one's stance.},
  archivePrefix = {arXiv},
  eprint = {2009.05198},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/NNREG934/Radha_2020_Information flow in political elections.pdf;/home/aleksandar/Zotero/storage/WKCMERVD/2009.html},
  journal = {arXiv:2009.05198 [physics, stat]},
  primaryClass = {physics, stat}
}

@article{rahmanStatisticallyEfficientScalable2020,
  title = {A {{Statistically Efficient}} and {{Scalable Method}} for {{Exploratory Analysis}} of {{High}}-{{Dimensional Data}}},
  author = {Rahman, Mohammad S. and Haffari, Gholamreza},
  year = {2020},
  month = feb,
  volume = {1},
  pages = {64},
  issn = {2661-8907},
  doi = {10.1007/s42979-020-0064-2},
  abstract = {Discovering associations among variables is an important data mining task. The associations can be considered as statistical dependencies among random variables, expressed as the structure of an underlying probabilistic graphical model. Current methods for graphical model structure discovery either do not scale well to datasets with large sample sizes, or suffer from high false discovery rates when the number of dimensions is much larger than the sample size. In this paper, we propose a scalable and statistically efficient approach for graphical model structure discovery for multivariate data involving continuous variables. Our approach uses a minimum message length (MML)-based objective, for which we design a greedy algorithm where the best edges maximising improvements to the MML-based score are added incrementally to the graphical model. We present extensive empirical results on synthetic data with different sample, variable, clique and inverse correlation coefficient and show that our method outperforms strong baselines in terms of both speed and the accuracy of the predicted associations among the random variables in the graphical model. We also report that our method performs significantly very well in AML, BRCA cancer data and other real-life datasets.},
  journal = {SN Computer Science},
  language = {en},
  number = {2}
}

@inproceedings{rahulCommunityDetectionUsing2021,
  title = {Community {{Detection Using Graphical Relationships}}},
  booktitle = {Inventive {{Communication}} and {{Computational Technologies}}},
  author = {{Rahul} and Bansal, Prateek and Goel, Priyam and Nayak, Purav},
  editor = {Ranganathan, G. and Chen, Joy and Rocha, {\'A}lvaro},
  year = {2021},
  pages = {985--996},
  publisher = {{Springer}},
  address = {{Singapore}},
  doi = {10.1007/978-981-15-7345-3_84},
  abstract = {Community detection in social networks requires a careful effort in capturing relationships between individual nodes and identifying the different communities in the network. Contemporary research in this field has so far not considered nodes to be belonging to multiple communities. In this paper, the Community Detection Problem is solved by converting the social network graph to a low-dimensional space of features is attempted. By adopting flexibility in exploring a node's neighbourhood, overlapping communities are captured. Two kinds of node neighbourhoods based on hop distance and functionality is defined and incorporated both local and global graph representation. Our algorithm is validated by applying it to large social network datasets and visualizing the number of clusters obtained. The clusters depict the various parameters on which the communities have been separated into. The larger the number of clusters, the larger is the complexity of the communities that the dataset has been separated into. On the whole, our work presents a novel approach towards community detection by using overlapping communities in a social network graph.},
  isbn = {9789811573453},
  language = {en},
  series = {Lecture {{Notes}} in {{Networks}} and {{Systems}}}
}

@article{raimbaultSpaceComplexitiesTerritorial,
  title = {Space and Complexities of Territorial Systems.},
  author = {Raimbault, Juste},
  doi = {arXiv:1901.09869v1},
  abstract = {{$<$}p{$>$}The spatial character of territorial systems plays a crucial role in the emergence of their complexities. This contribution aims at illustrating to what extent different types of complexities can be exhibited in models of such systems. We develop from a theoretical viewpoint some arguments illustrating ontological complexity, in the sense of the diversity and multidimensionality of possible representations, and then complexity in the sense of emergence, i.e. the necessity of the existence of several autonomous levels. We then propose numerical experiments to explore properties of complexity (dynamical complexity and co-evolution) within two simple models of urban morphogenesis. We finally suggest other dimensions of complexity which could be typical of territorial systems. {$<$}/p{$>$}},
  journal = {arXiv Physics and Society}
}

@inproceedings{rainfordSocioPhysicalModellingDeclining2020,
  title = {Socio-{{Physical Modelling}} and {{Declining Mobility}}},
  booktitle = {The 2020 {{Conference}} on {{Artificial Life}}},
  author = {Rainford, Penny Faulkner and Stepney, Susan and Merali, Yasmin},
  year = {2020},
  pages = {104--112},
  publisher = {{MIT Press}},
  address = {{Online}},
  doi = {10.1162/isal_a_00270},
  abstract = {We present a new modelling approach for complex systems incorporating a dynamic environment and individuals with agency. We do this through multiple models at different levels. We develop a common meta-model for these kinds of models. The meta-model captures the concepts of agents moving and interacting on a dynamic network, to provide the power of an agent based model situated in the context of a dynamic and changing environment. The addition of context allows us to isolate the decision process of the agent from the constraints and resources provided by the environment, so we can consider separately the effect of changes in the environment from changes in the agents' decision process, and changes caused by agents acting differently based on their learning from, and adapting to, the changed environment.},
  file = {/home/aleksandar/Zotero/storage/6IM3CZXQ/Rainford et al. - 2020 - Socio-Physical Modelling and Declining Mobility.pdf},
  language = {en}
}

@article{ramaziConvergenceLinearThreshold2020,
  title = {Convergence of Linear Threshold Decision-Making Dynamics in Finite Heterogeneous Populations},
  author = {Ramazi, Pouria and Cao, Ming},
  year = {2020},
  month = sep,
  volume = {119},
  pages = {109063},
  issn = {0005-1098},
  doi = {10.1016/j.automatica.2020.109063},
  abstract = {Linear threshold models have been studied extensively in structured populations; however, less attention is paid to perception differences among the individuals of the population. To focus on this effect, we exclude structure and consider a well-mixed population of heterogeneous agents, each associated with a threshold in the form of a fixed ratio within zero and one that can be unique to this agent. The agents are initialized with a choice of strategy A or B, and at each time step, one agent becomes active to update; if the ratio of agents playing A is higher (resp. lower) than her threshold, she updates to A (resp. B). We show that for any given initial condition, after a finite number of time steps, the population reaches an equilibrium where no agent's threshold is violated; however, the equilibrium is not necessarily uniquely determined by the initial condition but depends on the agents' activation sequence. We find all those possible equilibria that the dynamics may reach from a given initial condition and show that, in contrast to the case of homogeneous populations, heterogeneity in the agents' thresholds gives rise to several equilibria where both A-playing and B-playing agents coexist. Perception heterogeneity can, hence, preserve decision diversity, even in the absence of population structure. We also investigate the asymptotic stability of the equilibria and show how to calculate the contagion probability for a population with two thresholds.},
  file = {/home/aleksandar/Zotero/storage/U82ZSLGH/S0005109820302612.html},
  journal = {Automatica},
  language = {en}
}

@article{ramezaniJointInferenceStructure2020,
  title = {Joint {{Inference}} of {{Structure}} and {{Diffusion}} in {{Partially Observed Social Networks}}},
  author = {Ramezani, Maryam and Ziaei, Amirmohammad and Rabiee, Hamid R.},
  year = {2020},
  month = oct,
  abstract = {Access to complete data in large scale networks is often infeasible. Therefore, the problem of missing data is a crucial and unavoidable issue in analysis and modeling of real-world social networks. However, most of the research on different aspects of social networks do not consider this limitation. One effective way to solve this problem is to recover the missing data as a pre-processing step. The present paper tries to infer the unobserved data from both diffusion network and network structure by learning a model from the partially observed data. We develop a probabilistic generative model called "DiffStru" to jointly discover the hidden links of network structure and the omitted diffusion activities. The interrelations among links of nodes and cascade processes are utilized in the proposed method via learning coupled low dimensional latent factors. In addition to inferring the unseen data, the learned latent factors may also help network classification problems such as community detection. Simulation results on synthetic and real-world datasets show the excellent performance of the proposed method in terms of link prediction and discovering the identity and infection time of invisible social behaviors.},
  archivePrefix = {arXiv},
  eprint = {2010.01400},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Ramezani et al/Ramezani et al_2020_Joint Inference of Structure and Diffusion in Partially Observed Social Networks.pdf;/home/aleksandar/Zotero/storage/LPG2CQTQ/2010.html},
  journal = {arXiv:2010.01400 [cs]},
  primaryClass = {cs}
}

@article{ramosPowerLawsRoman2020,
  title = {Power Laws in the {{Roman Empire}}: A Survival Analysis},
  shorttitle = {Power Laws in the {{Roman Empire}}},
  author = {Ramos, Pedro L. and Costa, Luciano da F. and Louzada, Francisco and Rodrigues, Francisco A.},
  year = {2020},
  month = aug,
  abstract = {The Roman Empire shaped Western civilization, and many Roman principles are embodied in modern institutions. Although its political institutions proved both resilient and adaptable, allowing it to incorporate diverse populations, the Empire suffered from many internal conflicts. Indeed, most emperors died violently, from assassination, suicide, or in battle. These internal conflicts produced patterns in the length of time that can be identified by statistical analysis. In this paper, we study the underlying patterns associated with the reign of the Roman emperors by using statistical tools of survival data analysis. We consider all the 175 Roman emperors and propose a new power-law model with change points to predict the time-to-violent-death of the Roman emperors. This model encompasses data in the presence of censoring and long-term survivors, providing more accurate predictions than previous models. Our results show that power-law distributions can also occur in survival data, as verified in other data types from natural and artificial systems, reinforcing the ubiquity of power law distributions. The generality of our approach paves the way to further related investigations not only in other ancient civilizations but also in applications in engineering and medicine.},
  archivePrefix = {arXiv},
  eprint = {2008.10344},
  eprinttype = {arxiv},
  journal = {arXiv:2008.10344 [stat]},
  primaryClass = {stat}
}

@article{randlesDissonanceReductionSpecial2015,
  title = {Is Dissonance Reduction a Special Case of Fluid Compensation? {{Evidence}} That Dissonant Cognitions Cause Compensatory Affirmation and Abstraction.},
  shorttitle = {Is Dissonance Reduction a Special Case of Fluid Compensation?},
  author = {Randles, Daniel and Inzlicht, Michael and Proulx, Travis and Tullett, Alexa M. and Heine, Steven J.},
  year = {2015},
  volume = {108},
  pages = {697},
  publisher = {{American Psychological Association}},
  journal = {Journal of personality and social psychology},
  number = {5}
}

@article{raschkyInstitutionsLossesNatural2008,
  title = {Institutions and the Losses from Natural Disasters},
  author = {Raschky, P. A.},
  year = {2008},
  month = jul,
  volume = {8},
  pages = {627--634},
  publisher = {{Copernicus GmbH}},
  issn = {1561-8633},
  doi = {10.5194/nhess-8-627-2008},
  abstract = {{$<$}p{$><$}strong{$>$}Abstract.{$<$}/strong{$>$} Natural hazards can be seen as a function of a specific natural process and human (economic) activity. Whereby the bulk of literature on natural hazard management has its focus on the natural process, an increasing number of scholars is emphasizing the importance of human activity in this context. Existing literature has identified certain socio-economic factors that determine the impact of natural disasters on society. The purpose of this paper is to highlight the effects of the institutional framework that influences human behavior by setting incentives and to point out the importance of institutional vulnerability. Results from an empirical investigation of large scale natural disasters between 1984 and 2004 show that countries with better institutions experience less victims and lower economic losses from natural disasters. In addition, the results suggest a non-linear relationship between economic development and economic disaster losses. The suggestions in this paper have implications for the discussion on how to deal with the adverse effects of natural hazards and how to develop efficient adaption strategies.{$<$}/p{$>$}},
  file = {/home/aleksandar/Dropbox/Zotero/Raschky/Raschky_2008_Institutions and the losses from natural disasters.pdf},
  journal = {Natural Hazards and Earth System Sciences},
  language = {English},
  number = {4}
}

@article{rashidTerritoryPoliticsPower2015,
  title = {Territory, Politics of Power, and Physical Spatial Networks: {{The}} Case of {{Baghdad}}, {{Iraq}}},
  shorttitle = {Territory, Politics of Power, and Physical Spatial Networks},
  author = {Rashid, Mahbub and Alobaydi, Dhirgham},
  year = {2015},
  month = dec,
  volume = {50},
  pages = {180--194},
  issn = {01973975},
  doi = {10.1016/j.habitatint.2015.08.031},
  journal = {Habitat International},
  language = {en}
}

@techreport{rastNewFrontierStudying2020,
  title = {A {{New Frontier}} for {{Studying Within}}-{{Person Variability}}: {{Bayesian Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models}}},
  shorttitle = {A {{New Frontier}} for {{Studying Within}}-{{Person Variability}}},
  author = {Rast, Philippe and Martin, Stephen Ross and Liu, Siwei and Williams, Donald Ray},
  year = {2020},
  month = mar,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/j57pk},
  abstract = {Research on individual variation has received increased attention. The bulk of the models discussed in psychological research so far, focus mainly on the temporal development of the mean structure. We expand the view on the within-person residual variability and present a new model parameterization derived from classic multivariate GARCH models used to predict and forecast volatility in financial time-series. We propose a new pdBEKK and a modified DCC model that accommodate external time-varying predictors for the within-person variance. This main goal of this work is to evaluate the potential usefulness of MGARCH models for research in within-person variability. MGARCH models partition the within-person variance into, at least, three components: An overall constant and unconditional baseline variance, a process that introduces variance conditional on previous innovations, or random shocks, and a process that governs the carry-over effects of previous conditional variance, similar to an AR model. Moreover, these models allow for variance spill-over effects from one time-series to another. We illustrate the pdBEKK- and the DCC-MGARCH on two individuals who have rated their daily positive and negative affect over 100 consecutive days. The full models comprised a multivariate ARMA(1,1) model for the means and included physical activity as moderator of the overall baseline variance. Overall, the pdBEKK seems to result in a more straight forward psychological interpretation, but the DCC is generally easier to estimate and can accommodate more simultaneous time-series. Both models require rather large amounts of datapoints to detect non-zero parameters. Potentials and limitations are discussed. We provide an R-package bmgarch that facilitates the estimation of these types of models.},
  file = {/home/aleksandar/Dropbox/Zotero/Rast et al/Rast et al_2020_A New Frontier for Studying Within-Person Variability.pdf;/home/aleksandar/Dropbox/Zotero/Rast et al/Rast et al_2020_A New Frontier for Studying Within-Person Variability2.pdf},
  language = {en},
  type = {Preprint}
}

@article{raudenskaCrosscountryCrosstimeMeasurement,
  title = {The Cross-Country and Cross-Time Measurement Invariance of Positive and Negative Affect Scales: {{Evidence}} from {{European Social Survey}}},
  author = {Raudensk{\'a}, Petra},
  doi = {10.1016/j.ssresearch.2019.102369},
  abstract = {{$<$}p{$>$}Survey-based measures of subjective well-being are increasingly often analyzed cross-culturally. However, international comparison of these measures requires measurement invariance. Therefore, the major goal of this study is to investigate the cross-country and cross-time comparability of the 4-item positive and 7-item negative affect scales used in European Social Survey Round 3 (2006) and Round 6 (2012). This study applies both the traditional exact and the more recent Bayesian approximate approach to assess whether the affect scales are measurement invariant. The approximate approach detected several non-invariant items that are problematic for cross-national comparison and should be dropped from the scales. Consequently, measurement invariance was established in all countries over the two rounds for the reduced scales, allowing researchers to meaningfully compare their latent mean scores and the relationships with other theoretical constructs of interest. Thus, the study highlights the advantages of using multiple indicators and the necessity of measurement invariance testing in subjective well-being research.{$<$}/p{$>$}},
  journal = {Social Science Research}
}

@article{raudenskaCrosscountryCrosstimeMeasurement2019,
  title = {The Cross-Country and Cross-Time Measurement Invariance of Positive and Negative Affect Scales: {{Evidence}} from {{European Social Survey}}},
  shorttitle = {The Cross-Country and Cross-Time Measurement Invariance of Positive and Negative Affect Scales},
  author = {Raudensk{\'a}, Petra},
  year = {2019},
  month = oct,
  pages = {102369},
  issn = {0049-089X},
  doi = {10.1016/j.ssresearch.2019.102369},
  abstract = {Survey-based measures of subjective well-being are increasingly often analyzed cross-culturally. However, international comparison of these measures requires measurement invariance. Therefore, the major goal of this study is to investigate the cross-country and cross-time comparability of the 4-item positive and 7-item negative affect scales used in European Social Survey Round 3 (2006) and Round 6 (2012). This study applies both the traditional exact and the more recent Bayesian approximate approach to assess whether the affect scales are measurement invariant. The approximate approach detected several non-invariant items that are problematic for cross-national comparison and should be dropped from the scales. Consequently, measurement invariance was established in all countries over the two rounds for the reduced scales, allowing researchers to meaningfully compare their latent mean scores and the relationships with other theoretical constructs of interest. Thus, the study highlights the advantages of using multiple indicators and the necessity of measurement invariance testing in subjective well-being research.},
  file = {/home/aleksandar/Zotero/storage/GF25B9KN/S0049089X18309876.html},
  journal = {Social Science Research},
  language = {en}
}

@article{raudenskaCrosscountryCrosstimeMeasurementa,
  title = {The Cross-Country and Cross-Time Measurement Invariance of Positive and Negative Affect Scales: {{Evidence}} from {{European Social Survey}}},
  author = {Raudensk{\'a}, Petra},
  doi = {10.1016/j.ssresearch.2019.102369},
  abstract = {{$<$}p{$>$}Survey-based measures of subjective well-being are increasingly often analyzed cross-culturally. However, international comparison of these measures requires measurement invariance. Therefore, the major goal of this study is to investigate the cross-country and cross-time comparability of the 4-item positive and 7-item negative affect scales used in European Social Survey Round 3 (2006) and Round 6 (2012). This study applies both the traditional exact and the more recent Bayesian approximate approach to assess whether the affect scales are measurement invariant. The approximate approach detected several non-invariant items that are problematic for cross-national comparison and should be dropped from the scales. Consequently, measurement invariance was established in all countries over the two rounds for the reduced scales, allowing researchers to meaningfully compare their latent mean scores and the relationships with other theoretical constructs of interest. Thus, the study highlights the advantages of using multiple indicators and the necessity of measurement invariance testing in subjective well-being research.{$<$}/p{$>$}},
  journal = {Social Science Research}
}

@article{ravazziLearningHiddenInfluences2020,
  title = {Learning Hidden Influences in Large-Scale Dynamical Social Networks: {{A}} Data-Driven Sparsity-Based Approach},
  shorttitle = {Learning Hidden Influences in Large-Scale Dynamical Social Networks},
  author = {Ravazzi, Chiara and Dabbene, Fabrizio and Lagoa, Constantino and Proskurnikov, Anton V.},
  year = {2020},
  month = jul,
  abstract = {Interpersonal influence estimation from empirical data is a central challenge in the study of social structures and dynamics. Opinion dynamics theory is a young interdisciplinary science that studies opinion formation in social networks and has a huge potential in applications, such as marketing, advertisement and recommendations.},
  archivePrefix = {arXiv},
  eprint = {2007.06713},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/4WBI56SY/Ravazzi et al. - 2020 - Learning hidden influences in large-scale dynamica.pdf},
  journal = {arXiv:2007.06713 [cs, eess]},
  language = {en},
  primaryClass = {cs, eess}
}

@article{ravikumarHighDimensionalGraphicalModel2008,
  title = {High-{{Dimensional Graphical Model Selection Using}} \$\textbackslash ell\_1\$-{{Regularized Logistic Regression}}},
  author = {Ravikumar, Pradeep and Wainwright, Martin J. and Lafferty, John D.},
  year = {2008},
  month = apr,
  abstract = {We consider the problem of estimating the graph structure associated with a discrete Markov random field. We describe a method based on \$\textbackslash ell\_1\$-regularized logistic regression, in which the neighborhood of any given node is estimated by performing logistic regression subject to an \$\textbackslash ell\_1\$-constraint. Our framework applies to the high-dimensional setting, in which both the number of nodes \$p\$ and maximum neighborhood sizes \$d\$ are allowed to grow as a function of the number of observations \$n\$. Our main results provide sufficient conditions on the triple \$(n, p, d)\$ for the method to succeed in consistently estimating the neighborhood of every node in the graph simultaneously. Under certain assumptions on the population Fisher information matrix, we prove that consistent neighborhood selection can be obtained for sample sizes \$n = \textbackslash Omega(d\^3 \textbackslash log p)\$, with the error decaying as \$\textbackslash order(\textbackslash exp(-C n/d\^3))\$ for some constant \$C\$. If these same assumptions are imposed directly on the sample matrices, we show that \$n = \textbackslash Omega(d\^2 \textbackslash log p)\$ samples are sufficient.},
  archivePrefix = {arXiv},
  eprint = {0804.4202},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/6LGHZJ3C/0804.html},
  journal = {arXiv:0804.4202 [math, stat]},
  primaryClass = {math, stat}
}

@article{rawlingsCognitiveAuthorityConstraint2020,
  title = {Cognitive {{Authority}} and the {{Constraint}} of {{Attitude Change}} in {{Groups}}},
  author = {Rawlings, Craig M.},
  year = {2020},
  month = dec,
  volume = {85},
  pages = {992--1021},
  publisher = {{SAGE Publications Inc}},
  issn = {0003-1224},
  doi = {10.1177/0003122420967305},
  abstract = {Are individuals' attitudes constrained such that it is difficult to change one attitude without also changing other attitudes? Given a lack of longitudinal studies in real-world settings, it remains unclear if individuals have coherent attitude systems at all\textemdash and, if they do, what produces attitude constraint. I argue and show that groups can endogenously produce attitude constraint via cognitive authorities. Within groups, cognitive authorities explicitly link attitudes and generate feelings of connectedness among members, thereby facilitating the interpersonal processing of attitudes. Using data on interpersonal sentiment relations and attitude changes among members of intentional communities, I find cognitive authorities constrain attitudes via two mechanisms: (1) interpersonal tensions when attitudes and sentiment relations are misaligned (i.e., balance dynamics), and (2) social influence processes leading to attitude changes that are concordant with the group's attitude system (i.e., constraint satisfaction). These findings imply that attitude change models based exclusively on interpersonal contagion or individual drives for cognitive consistency overlook important ways group structures affect how individuals feel and think.},
  journal = {American Sociological Review},
  keywords = {attitude change,belief systems,group dynamics,social cohesion,social influence},
  language = {en},
  number = {6}
}

@article{rayInteroperableContextSensitive2007,
  title = {An Interoperable Context Sensitive Model of Trust},
  author = {Ray, Indrakshi and Ray, Indrajit and Chakraborty, Sudip},
  year = {2007},
  doi = {10.1007/s10844-007-0049-9},
  abstract = {Although the notion of trust is widely used in secure information systems, very few works attempt to formally define it or reason about it. Moreover, in most works, trust is defined as a binary concept\textemdash either an entity is completely trusted or not at all. Absolute trust on an entity requires one to have complete knowledge about the entity. This is rarely the case in real-world applications. Not trusting an entity, on the other hand, prohibits all communications with the entity rendering it useless. In short, treating trust as a binary concept is not acceptable in practice. Consequently, a model is needed that incorporates the notion of different degrees of trust. We propose a model that allows us to formalize trust relationships. The trust relationship between a truster and a trustee is associated with a context and depends on the experience, knowledge, and recommendation that the truster has with respect to the trustee in the given context. We show how our model can measure trust and compare two trust relationships in a given context. Sometimes enough information is not available about a given context to evaluate trust. Towards this end we show how the relationships between different contexts can be captured using a context graph. Formalizing the relationships between contexts allows us to extrapolate values from related contexts to approximate the trust of an entity even when all the information needed to calculate the trust is not available. Finally, we show how the semantic mismatch that arises because of different sources using different context graphs can be resolved and the trust of information obtained from these different sources compared.},
  file = {/home/aleksandar/Documents/Zotero/Ray et al/Ray et al_2007_An interoperable context sensitive model of trust.pdf},
  journal = {Journal of Intelligent Information Systems}
}

@book{rcoreteamLanguageEnvironmentStatistical2017,
  title = {R: {{A}} Language and Environment for Statistical Computing},
  author = {{R Core Team}},
  year = {2017},
  publisher = {{R Foundation for Statistical Computing}},
  address = {{Vienna}}
}

@book{reichBayesianStatisticalMethods2019,
  title = {Bayesian Statistical Methods},
  author = {Reich, Brian J and Ghosh, Sujit K},
  year = {2019},
  abstract = {Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models (GLM). The authors include many examples with complete R code and comparisons with analogous frequentist procedures. In addition to the basic concepts of Bayesian inferential methods, the book covers many general topics: Advice on selecting prior distributions Computational methods including Markov chain Monte Carlo (MCMC) Model-comparison and goodness-of-fit measures, including sensitivity to priors Frequentist properties of Bayesian methods Case studies covering advanced topics illustrate the flexibility of the Bayesian approach: Semiparametric regression Handling of missing data using predictive distributions Priors for high-dimensional regression models Computational techniques for large datasets Spatial data analysis The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets, and complete data analyses are available on the book's website. Brian J. Reich, Associate Professor of Statistics at North Carolina State University, is currently the editor-in-chief of the Journal of Agricultural, Biological, and Environmental Statistics and was awarded the LeRoy \& Elva Martin Teaching Award. Sujit K. Ghosh, Professor of Statistics at North Carolina State University, has over 22 years of research and teaching experience in conducting Bayesian analyses, received the Cavell Brownie mentoring award, and served as the Deputy Director at the Statistical and Applied Mathematical Sciences Institute.},
  annotation = {OCLC: 1097183939},
  isbn = {978-0-429-20229-2 978-0-429-51777-8 978-0-429-51091-5 978-0-429-51434-0},
  language = {English}
}

@article{reisGenerativeModelsSimultaneously2020,
  title = {Generative Models of Simultaneously Heavy-Tailed Distributions of Inter-Event Times on Nodes and Edges},
  author = {dos Reis, E. Fonseca and Li, A. and Masuda, N.},
  year = {2020},
  month = aug,
  abstract = {Intervals between discrete events representing human activities, as well as other types of events, often obey heavy-tailed distributions, and their impacts on collective dynamics on networks such as contagion processes have been intensively studied. The literature supports that such heavy-tailed distributions are present for inter-event times associated with both individual nodes and individual edges in networks. However, the simultaneous presence of heavy-tailed distributions of inter-event times for nodes and edges is a non-trivial phenomenon, and its origin has been elusive. In the present study, we propose a generative model and its variants to explain this phenomenon. We assume that each node independently transits between a high-activity and low-activity state according to a continuous-time two-state Markov process and that, for the main model, events on an edge occur at a high rate if and only if both end nodes of the edge are in the high-activity state. In other words, two nodes interact frequently only when both nodes prefer to interact with others. The model produces distributions of inter-event times for both individual nodes and edges that resemble heavy-tailed distributions across some scales. It also produces positive correlation in consecutive inter-event times, which is another stylized observation for empirical data of human activity. We expect that our modeling framework provides a useful benchmark for investigating dynamics on temporal networks driven by non-Poissonian event sequences.},
  archivePrefix = {arXiv},
  eprint = {2008.13034},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/AWYAU6EI/Reis et al_2020_Generative models of simultaneously heavy-tailed distributions of inter-event.pdf;/home/aleksandar/Zotero/storage/8XDCFYI3/2008.html},
  journal = {arXiv:2008.13034 [physics]},
  primaryClass = {physics}
}

@misc{RelationshipsSocialPhysical,
  title = {Relationships {{Between Social}}, {{Physical}}, and {{Psychological Factors}} in~{{Older Persons}}: {{Frailty}} as an {{Outcome}} in {{Network Analysis}} - {{ScienceDirect}}},
  file = {/home/aleksandar/Zotero/storage/S6S82JNE/S1525861020301936.html},
  howpublished = {https://www.sciencedirect.com/science/article/abs/pii/S1525861020301936}
}

@article{remer-bollowPartisanConsequencesLow,
  title = {Partisan Consequences of Low Turnout at Elections to the {{European Parliament}}},
  author = {{Remer-Bollow}, Uwe and Bernhagen, Patrick and Rose, Richard},
  doi = {10.1016/j.electstud.2019.02.003},
  abstract = {{$<$}h2{$>$}Abstract{$<$}/h2{$><$}p{$>$}Low turnout and potential differences in party preferences between voters and non-voters may affect party vote shares at European Parliament (EP) elections. Of particular concern is the rise of Eurosceptic and populist parties, but scholars do not know whether these would benefit from increased voter mobilization. To address this gap, we simulate the party choices of non-voters at the 2009 and 2014 EP elections. Contrary to analyses of turnout effects at general elections in multiparty systems, our simulations suggest that left-leaning and ideologically moderate parties would gain if turnout went up to levels observed at first-order national elections. And while there is some evidence that populist parties might have benefitted from higher turnout at the 2014 elections (but not in 2009), our findings do not support expectations that either Eurosceptic or Europhile parties' vote share would be affected by higher turnout.{$<$}/p{$>$}},
  journal = {Electoral Studies}
}

@article{remer-bollowPartisanConsequencesLowa,
  title = {Partisan Consequences of Low Turnout at Elections to the {{European Parliament}}},
  author = {{Remer-Bollow}, Uwe and Bernhagen, Patrick and Rose, Richard},
  doi = {10.1016/j.electstud.2019.02.003},
  abstract = {{$<$}h2{$>$}Abstract{$<$}/h2{$><$}p{$>$}Low turnout and potential differences in party preferences between voters and non-voters may affect party vote shares at European Parliament (EP) elections. Of particular concern is the rise of Eurosceptic and populist parties, but scholars do not know whether these would benefit from increased voter mobilization. To address this gap, we simulate the party choices of non-voters at the 2009 and 2014 EP elections. Contrary to analyses of turnout effects at general elections in multiparty systems, our simulations suggest that left-leaning and ideologically moderate parties would gain if turnout went up to levels observed at first-order national elections. And while there is some evidence that populist parties might have benefitted from higher turnout at the 2014 elections (but not in 2009), our findings do not support expectations that either Eurosceptic or Europhile parties' vote share would be affected by higher turnout.{$<$}/p{$>$}},
  journal = {Electoral Studies}
}

@article{renDetectingHierarchicalOverlapping2020,
  title = {Detecting {{Hierarchical}} and {{Overlapping Network Communities Based}} on {{Opinion Dynamics}}},
  author = {Ren, Ren and Shao, Jinliang and Yuhua, Cheng and Wang, Xiaofan},
  year = {2020},
  pages = {1--1},
  issn = {1558-2191},
  doi = {10.1109/TKDE.2020.3014329},
  abstract = {It is common for communities in real-world networks to possess hierarchical and overlapping structures, which make community detection even more challenging. In this paper, by investigating consensus process of the classical DeGroot model in opinion dynamics, we propose a novel method based on the cumulative opinion distance (COD) to discover hierarchical and overlapping communities. It is shown that this method is different from those classical algorithms relying on static fitness metrics that depict the inhomogeneous connectivity across the network. The proposed method is validated from two aspects. First, by estimating the eigenvectors of adjacency matrices, we investigate the detectability limit of our algorithms on random networks, which together with the results concerning the convergence speed of consensus guarantees the performance of our method theoretically. Second, experiments on both \textbackslash tcblarge scale real-world networks and artificial benchmarks show that our method is very effective and competitive on hierarchical modular graphs. In particular, it outperforms the state-of-the-art algorithms on overlapping community detection.},
  file = {/home/aleksandar/Zotero/storage/875DBDUB/9159919.html},
  journal = {IEEE Transactions on Knowledge and Data Engineering}
}

@article{renModelingInfluencePublic2020,
  title = {Modeling the {{Influence}} of {{Public Risk Perceptions}} on the {{Adoption}} of {{Green Stormwater Infrastructure}}: {{An Application}} of {{Bayesian Belief Networks Versus Logistic Regressions}} on a {{Statewide Survey}} of {{Households}} in {{Vermont}}},
  shorttitle = {Modeling the {{Influence}} of {{Public Risk Perceptions}} on the {{Adoption}} of {{Green Stormwater Infrastructure}}},
  author = {Ren, Qing and Zia, Asim and Rizzo, Donna M. and Mathews, Nancy},
  year = {2020},
  month = oct,
  volume = {12},
  pages = {2793},
  issn = {2073-4441},
  doi = {10.3390/w12102793},
  abstract = {There is growing environmental psychology and behavior literature with mixed empirical evidence about the influence of public risk perceptions on the adoption of environmentally friendly ``green behaviors''. Adoption of stormwater green infrastructure on residential properties, while costlier in the short term compared to conventional greywater infrastructure, plays an important role in the reduction of nutrient loading from non-point sources into freshwater rivers and lakes. In this study, we use Bayesian Belief Networks (BBNs) to analyze a 2015 survey dataset (sample size = 472 respondents) about the adoption of green infrastructure (GSI) in Vermont's residential areas, most of which are located in either the Lake Champlain Basin or Connecticut River Basin. Eight categories of GSI were investigated: roof diversion, permeable pavement, infiltration trenches, green roofs, rain gardens, constructed wetlands, tree boxes, and others. Using both unsupervised and supervised machine learning algorithms, we used Bayesian Belief Networks to quantify the influence of public risk perceptions on GSI adoption while accounting for a range of demographic and spatial variables. We also compare the effectiveness of the Bayesian Belief Network approach and logistic regression in predicting the pro-environmental behaviors (adoption of GSI). The results show that influencing factors for current adoption differ by the type of GSI. Increased perception of risk from stormwater issues is associated with the adoption of rain gardens and infiltration trenches. Runoff issues are more likely to be considered the governments' (town, state, and federal agencies) responsibility, whereas lawn erosion is more likely to be considered the residents' responsibility. When using the same set of variables to predict pro-environmental behaviors (adoption of GSI), the BBN approach produces more accurate predictions compared to logistic regression. The results provide insights for further research on how to encourage residents to take measures for mitigating stormwater issues and stormwater management.},
  file = {/home/aleksandar/Zotero/storage/DFBIQD5N/Ren et al. - 2020 - Modeling the Influence of Public Risk Perceptions .pdf},
  journal = {Water},
  language = {en},
  number = {10}
}

@article{reuningExploringDynamicsLatent2019,
  title = {Exploring the {{Dynamics}} of {{Latent Variable Models}}},
  author = {Reuning, Kevin and Kenwick, Michael R. and Fariss, Christopher J.},
  year = {2019},
  month = oct,
  volume = {27},
  pages = {503--517},
  issn = {1047-1987, 1476-4989},
  doi = {10.1017/pan.2019.1},
  abstract = {Researchers face a tradeoff when applying latent variable models to time-series, cross-sectional data. Static models minimize bias but assume data are temporally independent, resulting in a loss of efficiency. Dynamic models explicitly model temporal data structures, but smooth estimates of the latent trait across time, resulting in bias when the latent trait changes rapidly. We address this tradeoff by investigating a new approach for modeling and evaluating latent variable estimates: a robust dynamic model. The robust model is capable of minimizing bias and accommodating volatile changes in the latent trait. Simulations demonstrate that the robust model outperforms other models when the underlying latent trait is subject to rapid change, and is equivalent to the dynamic model in the absence of volatility. We reproduce latent estimates from studies of judicial ideology and democracy. For judicial ideology, the robust model uncovers shocks in judicial voting patterns that were not previously identified in the dynamic model. For democracy, the robust model provides more precise estimates of sudden institutional changes such as the imposition of martial law in the Philippines (1972\textendash 1981) and the short-lived Saur Revolution in Afghanistan (1978). Overall, the robust model is a useful alternative to the standard dynamic model for modeling latent traits that change rapidly over time.},
  file = {/home/aleksandar/Zotero/storage/B2IHAQ33/CBE116F37900DAE957B2D7EB53DB0907.html},
  journal = {Political Analysis},
  language = {en},
  number = {4}
}

@techreport{rexinFindingYourWay2020,
  title = {Finding {{Your Way}}: {{Shortest Paths}} on {{Networks}}},
  shorttitle = {Finding {{Your Way}}},
  author = {Rexin, Teresa and Porter, Mason A.},
  year = {2020},
  month = nov,
  institution = {{SocArXiv}},
  doi = {10.31235/osf.io/s34uv},
  abstract = {Traveling to different destinations is a big part of our lives. How do we know the best way to navigate from one place to another? Perhaps we could test all of the different ways of traveling between two places, but another method is using mathematics and computation to find a shortest path. We discuss how to find a shortest path and introduce Dijkstra's algorithm to minimize the total cost of a path, where the cost may be the travel distance or travel time. We also discuss how shortest paths can be used in the real world to save time and increase traveling efficiency.},
  file = {/home/aleksandar/Zotero/storage/XNMTWARP/Rexin and Porter - 2020 - Finding Your Way Shortest Paths on Networks.pdf},
  language = {en},
  type = {Preprint}
}

@article{reyeroEvolutionPoliticalOpinion2020,
  title = {Evolution of the Political Opinion Landscape during Electoral Periods},
  author = {Reyero, Tom{\'a}s Mussi and Beir{\'o}, Mariano G. and {Alvarez-Hamelin}, J. Ignacio and Hern{\'a}ndez, Laura and Kotzinos, Dimitris},
  year = {2020},
  month = nov,
  abstract = {We present a study of the evolution of the political landscape during the 2015 and 2019 presidential elections in Argentina, based on the data obtained from the micro-blogging platform Twitter. We build a semantic network based on the hashtags used by all the users following at least one of the main candidates. With this network we can detect the topics that are discussed in the society. At a difference with most studies of opinion on social media, we do not choose the topics a priori, they naturally emerge from the community structure of the semantic network instead. We assign to each user a dynamical topic vector which measures the evolution of her/his opinion in this space and allows us to monitor the similarities and differences among groups of supporters of different candidates. Our results show that the method is able to detect the dynamics of formation of opinion on different topics and, in particular, it can capture the reshaping of the political opinion landscape which has led to the inversion of result between the two rounds of the 2015 election.},
  archivePrefix = {arXiv},
  eprint = {2011.09538},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/KZ4SWGHG/Reyero et al. - 2020 - Evolution of the political opinion landscape durin.pdf},
  journal = {arXiv:2011.09538 [cs]},
  keywords = {Computer Science - Social and Information Networks},
  language = {en},
  primaryClass = {cs}
}

@article{rhemtullaWorseMeasurementError,
  title = {Worse {{Than Measurement Error}}},
  author = {Rhemtulla, Mijke and {van Bork}, Riet and Borsboom, Denny},
  doi = {10.31219/osf.io/42s8b},
  abstract = {Previous research and methodological advice has focused on the importance of accounting for measurement error in psychological data. That perspective assumes that psychological variables conform to a common factor model, such that they consist of construct variance plus error. In this paper, we explore what happens when a set of items that are not generated from a common factor construct model are nonetheless modeled as reflecting a common factor. Through a series of hypothetical examples and an empirical re-analysis, we show that (1) common factor models tend to produce extremely biased and highly variable structural parameter estimates when the population model is not a common factor model; (2) model fit is a poor indicator of the degree of bias; and (3) composite models are sometimes more reliable than common factor models under alternative measurement structures, though they also lead to unacceptably bad solutions in some cases.}
}

@article{richardson2014complex,
  title = {Complex Dynamical Systems in Social and Personality Psychology: {{Theory}}, Modeling, and Analysis.},
  author = {Richardson, Michael J and Dale, Rick and Marsh, Kerry L},
  year = {2014},
  publisher = {{Cambridge University Press}},
  file = {/home/aleksandar/Zotero/storage/5E8CDZE9/Handbook of Research Methods in Social and Personality Psychology by Harry T. Reis, Charles M. Judd (eds.) (z-lib.org).epub}
}

@article{ricklesSimpleGuideChaos2007,
  title = {A Simple Guide to Chaos and Complexity},
  author = {Rickles, Dean and Hawe, Penelope and Shiell, Alan},
  year = {2007},
  month =