text:
2019},
  month = nov,
  abstract = {There has been a tremendous methodological development of Bayes factors for hypothesis testing in the social and behavioral sciences, and related fields. This development is due to the flexibility of the Bayes factor for testing multiple hypotheses simultaneously, the ability to test complex hypotheses involving equality as well as order constraints on the parameters of interest, and the interpretability of the outcome as the weight of evidence provided by the data in support of competing scientific theories. The available software tools for Bayesian hypothesis testing are still limited however. In this paper we present a new R-package called BFpack that contains functions for Bayes factor hypothesis testing for the many common testing problems. The software includes novel tools (i) for Bayesian exploratory testing (null vs positive vs negative effects), (ii) for Bayesian confirmatory testing (competing hypotheses with equality and/or order constraints), (iii) for common statistical analyses, such as linear regression, generalized linear models, (multivariate) analysis of (co)variance, correlation analysis, and random intercept models, (iv) using default priors, and (v) while allowing data to contain missing observations that are missing at random.},
  archivePrefix = {arXiv},
  eprint = {1911.07728},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Dropbox/Zotero/Mulder et al/Mulder et al_2019_BFpack.pdf},
  journal = {arXiv:1911.07728 [stat]},
  language = {en},
  primaryClass = {stat}
}

@article{mulderGeneralizationSavageDickeyDensity2020,
  title = {A {{Generalization}} of the {{Savage}}-{{Dickey Density Ratio}} for {{Testing Equality}} and {{Order Constrained Hypotheses}}},
  author = {Mulder, J. and Wagenmakers, E.-J. and Marsman, M.},
  year = {2020},
  month = apr,
  abstract = {The Savage-Dickey density ratio is a specific expression of the Bayes factor when testing a precise (equality constrained) hypothesis against an unrestricted alternative. The expression greatly simplifies the computation of the Bayes factor at the cost of assuming a specific form of the prior under the precise hypothesis as a function of the unrestricted prior. A generalization was proposed by Verdinelli and Wasserman (1995) such that the priors can be freely specified under both hypotheses while keeping the computational advantage. This paper presents an extension of this generalization when the hypothesis has equality as well as order constraints on the parameters of interest. The methodology is used for a constrained multivariate t test using the JZS Bayes factor and a constrained hypothesis test under the multinomial model.},
  archivePrefix = {arXiv},
  eprint = {2004.09899},
  eprinttype = {arxiv},
  journal = {arXiv:2004.09899 [stat]},
  primaryClass = {stat}
}

@article{mulderPrevalenceInformationInconsistency2020,
  title = {On the Prevalence of Information Inconsistency in Normal Linear Models},
  author = {Mulder, Joris and Berger, James O. and Pe{\~n}a, V{\'i}ctor and Bayarri, M. J.},
  year = {2020},
  month = feb,
  issn = {1863-8260},
  doi = {10.1007/s11749-020-00704-4},
  abstract = {Informally, `information inconsistency' is the property that has been observed in some Bayesian hypothesis testing and model selection scenarios whereby the Bayesian conclusion does not become definitive when the data seem to become definitive. An example is that, when performing a t test using standard conjugate priors, the Bayes factor of the alternative hypothesis to the null hypothesis remains bounded as the t statistic grows to infinity. The goal of this paper is to thoroughly investigate information inconsistency in various Bayesian testing problems. We consider precise hypothesis tests, one-sided hypothesis tests, and multiple hypothesis tests under normal linear models with dependent observations. Standard priors are considered, such as conjugate and semi-conjugate priors, as well as variations of Zellner's g prior (e.g., fixed g priors, mixtures of g priors, and adaptive (data-based) g priors). It is shown that information inconsistency is a widespread problem using standard priors while certain theoretically recommended priors, including scale mixtures of conjugate priors and adaptive priors, are information consistent.},
  journal = {TEST},
  language = {en}
}

@article{mullerFilterBubblesEcho2020,
  title = {Filter {{Bubbles}}, {{Echo Chambers}}, and {{Reinforcement}}: {{Tracing Populism}} in {{Election Data}}},
  shorttitle = {Filter {{Bubbles}}, {{Echo Chambers}}, and {{Reinforcement}}},
  author = {M{\"u}ller, Johannes and H{\"o}sel, Volker and Tellier, Aur{\'e}lien},
  year = {2020},
  month = jul,
  abstract = {We present a novel model for the effect of echo chambers, filter bubbles, and reinforcement on election results. Our model extends the well known voter model with zealots to include reinforcement. We analyze the behaviour of the model, determine the invariant measure, and show that reinforcement may 1) shift the distribution of votes compared to the voter model, and 2) lead to phase transitions. We test whether the model with reinforcement fit better than under its absence in election data from US presidential elections, the Brexit referendum, and parliamentary elections in France, The Netherlands, and Germany. We find in many cases that populist parties and candidates can be clearly identified by a high level of reinforcement. Furthermore, we find the phase transition predicted by the model back in data. We finally discuss the implications and relevance of our findings and possible origins of the reinforcement behaviour in modern societies.},
  archivePrefix = {arXiv},
  eprint = {2007.03910},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Dropbox/Zotero/Müller et al/Müller et al_2020_Filter Bubbles, Echo Chambers, and Reinforcement.pdf;/home/aleksandar/Zotero/storage/TMT2DN7B/2007.html},
  journal = {arXiv:2007.03910 [physics]},
  primaryClass = {physics}
}

@article{mullickActiveabsorbingPhaseTransition,
  title = {Active-Absorbing Phase Transition and Small-World Behaviour in {{Ising}} Model on Finite Addition Type Networks in Two Dimensions},
  author = {Mullick, Pratik and Sen, Parongama},
  doi = {10.1093/comnet/cnz046},
  abstract = {We consider the ordering dynamics of the Ising model on a square lattice where an additional fixed number of bonds connect any two sites chosen randomly from a total of |\$N\$| lattice sites. The total number of shortcuts added is controlled by two parameters |\$p\$| and |\$\textbackslash alpha\$| for fixed |\$N\$|\nolinebreak. The structural properties of the network are investigated which show that the small-world behaviour is obtained along the line |\$\textbackslash alpha=\textbackslash frac\{\textbackslash ln (N/2p)\}\{\textbackslash ln N\}\$|\nolinebreak, which separates regions with ultra-small world like behaviour and short-ranged lattice like behaviour. We obtain a rich phase diagram in the |\$p-\textbackslash alpha\$| plane showing the existence of different types of active and absorbing states to which the Ising model evolves to and their boundaries.},
  journal = {Journal of Complex Networks}
}

@article{mullickActiveabsorbingPhaseTransitiona,
  title = {Active-Absorbing Phase Transition and Small-World Behaviour in {{Ising}} Model on Finite Addition Type Networks in Two Dimensions},
  author = {Mullick, Pratik and Sen, Parongama},
  doi = {10.1093/comnet/cnz046},
  abstract = {We consider the ordering dynamics of the Ising model on a square lattice where an additional fixed number of bonds connect any two sites chosen randomly from a total of |\$N\$| lattice sites. The total number of shortcuts added is controlled by two parameters |\$p\$| and |\$\textbackslash alpha\$| for fixed |\$N\$|\nolinebreak. The structural properties of the network are investigated which show that the small-world behaviour is obtained along the line |\$\textbackslash alpha=\textbackslash frac\{\textbackslash ln (N/2p)\}\{\textbackslash ln N\}\$|\nolinebreak, which separates regions with ultra-small world like behaviour and short-ranged lattice like behaviour. We obtain a rich phase diagram in the |\$p-\textbackslash alpha\$| plane showing the existence of different types of active and absorbing states to which the Ising model evolves to and their boundaries.},
  journal = {Journal of Complex Networks}
}

@article{mullickActiveabsorbingPhaseTransitionb,
  title = {Active-Absorbing Phase Transition and Small-World Behaviour in {{Ising}} Model on Finite Addition Type Networks in Two Dimensions},
  author = {Mullick, Pratik and Sen, Parongama},
  doi = {10.1093/comnet/cnz046},
  abstract = {We consider the ordering dynamics of the Ising model on a square lattice where an additional fixed number of bonds connect any two sites chosen randomly from a total of |\$N\$| lattice sites. The total number of shortcuts added is controlled by two parameters |\$p\$| and |\$\textbackslash alpha\$| for fixed |\$N\$|\nolinebreak. The structural properties of the network are investigated which show that the small-world behaviour is obtained along the line |\$\textbackslash alpha=\textbackslash frac\{\textbackslash ln (N/2p)\}\{\textbackslash ln N\}\$|\nolinebreak, which separates regions with ultra-small world like behaviour and short-ranged lattice like behaviour. We obtain a rich phase diagram in the |\$p-\textbackslash alpha\$| plane showing the existence of different types of active and absorbing states to which the Ising model evolves to and their boundaries.},
  journal = {Journal of Complex Networks}
}

@misc{MultipleDimensionsAttitudes,
  title = {Multiple Dimensions of Attitudes about Homosexuality: Development of a Multifaceted Scale Measuring Attitudes toward Homosexuality. - {{PubMed}} - {{NCBI}}},
  file = {/home/aleksandar/Zotero/storage/6WFLVYML/21058145.html},
  howpublished = {https://www.ncbi.nlm.nih.gov/pubmed/21058145}
}

@article{munjalEvidenceOstwaldRipening,
  title = {Evidence of {{Ostwald Ripening}} in Opinion Driven Dynamics of Mutually Competitive Social Networks},
  author = {Munjal, Puja and Kumar, Lalit and Kumar, Sandeep and Banati, Hema},
  doi = {S0378437119301153},
  abstract = {{$<$}p{$>$}Publication date: Available online 1 February 2019{$<$}/p{$><$}p{$>$}\textbf{Source:} Physica A: Statistical Mechanics and its Applications{$<$}/p{$><$}p{$>$}Author(s): Puja Munjal, Lalit Kumar, Sandeep Kumar, Hema Banati{$<$}/p{$><$}h5{$>$}Abstract{$<$}/h5{$><$}div{$><$}p{$>$}Models based on opinion exchange aim to describe the dynamics of social networks and to uncover the intrinsic mechanisms in mutually competitive social networks (MCSN). However, the limited capability of the existing opinion exchange models for characterizing the real world social networks has triggered the need for more realistic models. In this paper, the natural phenomenon of Ostwald ripening is explored to explain the generally observed process related to growth of bigger social networks at the expense of smaller social networks. A novel model called Ostwald Ripening Social Network (ORSN) is developed, for understanding the opinion driven growth dynamics of real-world MCSN. Ostwald ripening phenomenon has been extensively used to explain the growth of particles at nanoscale. In order to get better insight of the phenomenon, we synthesized Zinc oxide (ZnO) nanoparticles and a thorough investigation is done to understand the growth dynamics under varied condition of temperature. Strong experimentation is done on the extensive data set collected from actual social network, based on the opinion formation under the influence of factors like propaganda and network ties. The results of the growth dynamics from actually synthesized nanoparticles are found in corroboration with the pattern of growth dynamics of the MCSN. This is a vital attempt to complement the existing approaches, with a conceptual understanding that would help the supervision, prediction and control of dynamic processes in social networks.{$<$}/p{$><$}/div{$>$}},
  journal = {Physica A: Statistical Mechanics and its Applications}
}

@article{munjalEvidenceOstwaldRipeninga,
  title = {Evidence of {{Ostwald Ripening}} in Opinion Driven Dynamics of Mutually Competitive Social Networks},
  author = {Munjal, Puja and Kumar, Lalit and Kumar, Sandeep and Banati, Hema},
  doi = {S0378437119301153},
  abstract = {{$<$}p{$>$}Publication date: Available online 1 February 2019{$<$}/p{$><$}p{$>$}\textbf{Source:} Physica A: Statistical Mechanics and its Applications{$<$}/p{$><$}p{$>$}Author(s): Puja Munjal, Lalit Kumar, Sandeep Kumar, Hema Banati{$<$}/p{$><$}h5{$>$}Abstract{$<$}/h5{$><$}div{$><$}p{$>$}Models based on opinion exchange aim to describe the dynamics of social networks and to uncover the intrinsic mechanisms in mutually competitive social networks (MCSN). However, the limited capability of the existing opinion exchange models for characterizing the real world social networks has triggered the need for more realistic models. In this paper, the natural phenomenon of Ostwald ripening is explored to explain the generally observed process related to growth of bigger social networks at the expense of smaller social networks. A novel model called Ostwald Ripening Social Network (ORSN) is developed, for understanding the opinion driven growth dynamics of real-world MCSN. Ostwald ripening phenomenon has been extensively used to explain the growth of particles at nanoscale. In order to get better insight of the phenomenon, we synthesized Zinc oxide (ZnO) nanoparticles and a thorough investigation is done to understand the growth dynamics under varied condition of temperature. Strong experimentation is done on the extensive data set collected from actual social network, based on the opinion formation under the influence of factors like propaganda and network ties. The results of the growth dynamics from actually synthesized nanoparticles are found in corroboration with the pattern of growth dynamics of the MCSN. This is a vital attempt to complement the existing approaches, with a conceptual understanding that would help the supervision, prediction and control of dynamic processes in social networks.{$<$}/p{$><$}/div{$>$}},
  journal = {Physica A: Statistical Mechanics and its Applications}
}

@article{munozUnexpectedEventSurveyundefined/ed,
  title = {Unexpected {{Event}} during {{Survey Design}}: {{Promise}} and {{Pitfalls}} for {{Causal Inference}}},
  shorttitle = {Unexpected {{Event}} during {{Survey Design}}},
  author = {Mu{\~n}oz, Jordi and {Falc{\'o}-Gimeno}, Albert and Hern{\'a}ndez, Enrique},
  year = {undefined/ed},
  pages = {1--21},
  issn = {1047-1987, 1476-4989},
  doi = {10.1017/pan.2019.27},
  abstract = {An increasing number of studies exploit the occurrence of unexpected events during the fieldwork of public opinion surveys to estimate causal effects. In this paper, we discuss the use of this identification strategy based on unforeseen and salient events that split the sample of respondents into treatment and control groups: the Unexpected Event during Survey Design. In particular, we focus on the assumptions under which unexpected events can be exploited to estimate causal effects and we discuss potential threats to identification, paying especial attention to the observable and testable implications of these assumptions. We propose a series of best practices in the form of various estimation strategies and robustness checks that can be used to lend credibility to the causal estimates. Drawing on data from the European Social Survey, we illustrate the discussion of this method with an original study of the impact of the Charlie Hebdo terrorist attacks (Paris, 01/07/2015) on French citizens' satisfaction with their national government.},
  file = {/home/aleksandar/Zotero/storage/GBZNVKFK/E9DB24A62172D1EB2116FEFFEAE45998.html},
  journal = {Political Analysis},
  language = {en}
}

@inproceedings{muraliOnlineLocalCommunities2020,
  title = {Online Local Communities with Motifs},
  booktitle = {2020 {{Second International Conference}} on {{Transdisciplinary AI}} ({{TransAI}})},
  author = {Murali, M. and Potika, K. and Pollett, C.},
  year = {2020},
  month = sep,
  pages = {59--66},
  doi = {10.1109/TransAI49837.2020.00014},
  abstract = {A community in a network is a set of nodes that are densely and closely connected within the set, yet sparsely connected to nodes outside of it. Detecting communities in large networks helps solve many real-world problems. However, detecting such communities in a complex network by focusing on the whole network is costly. Instead, one can focus on finding overlapping communities starting from one or more seed nodes of interest. Moreover, on the online setting the network is given as a stream of higher order structures, i.e., triangles of nodes to be clustered into communities.In this paper, we propose an on online local graph community detection algorithm that uses motifs, such as triangles of nodes. We provide experimental results and compare it to another algorithm named COEUS. We use two public datasets, one of Amazon data and the other of DBLP data. Furthermore, we create and experiment on a new dataset that consists of web pages and their links by using the Internet Archive. This latter dataset provides insights to better understand how working with motifs is different than working with edges.},
  file = {/home/aleksandar/Zotero/storage/TG4KL3SJ/9253150.html},
  keywords = {Community detection,graph streams,Higher order structures,Local communities,Motifs,Online community,seed sets,Triangles}
}

@article{murphyMultimodalNetworkDynamics2020,
  title = {Multimodal Network Dynamics Underpinning Working Memory},
  author = {Murphy, Andrew C. and Bertolero, Maxwell A. and Papadopoulos, Lia and {Lydon-Staley}, David M. and Bassett, Danielle S.},
  year = {2020},
  month = jun,
  volume = {11},
  pages = {3035},
  publisher = {{Nature Publishing Group}},
  issn = {2041-1723},
  doi = {10.1038/s41467-020-15541-0},
  abstract = {Complex human cognition arises from the integrated processing of multiple brain systems. However, little is known about how brain systems and their interactions might relate to, or perhaps even explain, human cognitive capacities. Here, we address this gap in knowledge by proposing a mechanistic framework linking frontoparietal system activity, default mode system activity, and the interactions between them, with individual differences in working memory capacity. We show that working memory performance depends on the strength of functional interactions between the frontoparietal and default mode systems. We find that this strength is modulated by the activation of two newly described brain regions, and demonstrate that the functional role of these systems is underpinned by structural white matter. Broadly, our study presents a holistic account of how regional activity, functional connections, and structural linkages together support integrative processing across brain systems in order for the brain to execute a complex cognitive process.},
  copyright = {2020 The Author(s)},
  file = {/home/aleksandar/Dropbox/Zotero/Murphy et al/Murphy et al_2020_Multimodal network dynamics underpinning working memory.pdf;/home/aleksandar/Zotero/storage/53AQ4AQU/s41467-020-15541-0.html},
  journal = {Nature Communications},
  language = {en},
  number = {1}
}

@article{muthenNewMethodsStudy,
  ids = {muthenNewMethodsStudya},
  title = {New {{Methods}} for the {{Study}} of {{Measurement Invariance}} with {{Many Groups}}},
  author = {Muthen, Bengt and Asparouhov, Tihomir},
  pages = {60},
  file = {/home/aleksandar/Dropbox/Zotero/Muthen_Asparouhov/Muthen_Asparouhov_New Methods for the Study of Measurement Invariance with Many Groups.pdf;/home/aleksandar/Dropbox/Zotero/Muthen_Asparouhov/Muthen_Asparouhov_New Methods for the Study of Measurement Invariance with Many Groups2.pdf},
  language = {en}
}

@article{n.zehmakanRumorSpreadingTrigger2020,
  title = {Rumor Spreading: {{A}} Trigger for Proliferation or Fading Away},
  shorttitle = {Rumor Spreading},
  author = {N. Zehmakan, Ahad and Galam, Serge},
  year = {2020},
  month = jul,
  volume = {30},
  pages = {073122},
  publisher = {{American Institute of Physics}},
  issn = {1054-1500},
  doi = {10.1063/5.0006984},
  abstract = {The dynamics of rumor spreading is investigated using a model with three kinds of agents who are, respectively, the Seeds, the Agnostics, and the Others. While Seeds are the ones who start spreading the rumor being adamantly convinced of its truth, Agnostics reject any kind of rumor and do not believe in conspiracy theories. In between, the Others constitute the main part of the community. While Seeds are always Believers and Agnostics are always Indifferents, Others can switch between being Believer and Indifferent depending on who they are discussing with. The underlying driving dynamics is implemented via local updates of randomly formed groups of agents. In each group, an Other turns into a Believer as soon as mm{$<$}math display="inline" overflow="scroll" altimg="eq-00001.gif"{$>$} {$<$}mi{$>$}m{$<$}/mi{$><$}/math{$>$} or more Believers are present in the group. However, since some Believers may lose interest in the rumor as time passes by, we add a flipping fixed rate 0},
  file = {/home/aleksandar/Dropbox/Zotero/N. Zehmakan_Galam/N. Zehmakan_Galam_2020_Rumor spreading.pdf;/home/aleksandar/Zotero/storage/UIRMKQBC/5.html},
  journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  number = {7}
}

@article{nadeauAreElectionResults2019,
  title = {Are Election Results More Unpredictable? {{A}} Forecasting Test},
  shorttitle = {Are Election Results More Unpredictable?},
  author = {Nadeau, Richard and Dassonneville, Ruth and {Lewis-Beck}, Michael S. and Mongrain, Philippe},
  year = {2019},
  month = may,
  pages = {1--8},
  issn = {2049-8470, 2049-8489},
  doi = {10.1017/psrm.2019.24},
  journal = {Political Science Research and Methods},
  language = {en}
}

@article{nadeauElectionForecastsCracking2020,
  title = {Election Forecasts: {{Cracking}} the {{Danish}} Case},
  shorttitle = {Election Forecasts},
  author = {Nadeau, Richard and {Lewis-Beck}, Michael S.},
  year = {2020},
  month = apr,
  issn = {0169-2070},
  doi = {10.1016/j.ijforecast.2019.09.007},
  abstract = {Election forecasting models based on voting theories and estimated via regression analysis are routinely available for virtually all advanced industrial democracies. Denmark, however, offers an exception, for no such prediction equations have been published on the Danish case. This absence has sometimes been attributed to the puzzling nature of economic voting there, along with the complexity of its multi-party system, which renders formulation of the dependent variable problematic. We attempt to overcome these obstacles, offering a ``synthetic'' forecasting model for Danish national election outcomes, 1964\textendash 2015. The regression model, based on the variables of economic growth and vote intention, performs well, by various tests. Finally, we apply it, ex ante fashion, to the 2019 contest, where the prediction favored the Social Democratic led coalition, an outcome that came to pass.},
  file = {/home/aleksandar/Zotero/storage/7X5ZWCE8/S0169207019302535.html},
  journal = {International Journal of Forecasting},
  language = {en}
}

@article{nannestadWhatHaveWe2008,
  title = {What {{Have We Learned About Generalized Trust}}, {{If Anything}}?},
  author = {Nannestad, Peter},
  year = {2008},
  volume = {11},
  pages = {413--436},
  doi = {10.1146/annurev.polisci.11.060606.135412},
  abstract = {After discussing issues related to the conceptualization, measurement, and statistical analysis of data on generalized trust, I survey recent empirical work (mainly from about 2000\textendash 2007) on this topic. First, results concerning cross-country differences in the level of generalized trust and the dynamics of these levels are presented. Then comes an investigation of empirical work on the determinants of generalized trust, covering contributions focusing on the impact of civic society, quality of institutions, culture and values, and ethnic heterogeneity. In these studies, generalized trust is treated as the dependent variable. After that, I survey recent empirical work on societal impacts of generalized trust, covering research on the impact of generalized trust on economic outcomes, on politics and ``good government,'' and on the welfare state. Here, generalized trust is treated as an independent variable. I conclude with a short assessment of where we stand and how research on generalized trust may proceed from here.},
  annotation = {\_eprint: https://doi.org/10.1146/annurev.polisci.11.060606.135412},
  file = {/home/aleksandar/Dropbox/Zotero/Nannestad/Nannestad_2008_What Have We Learned About Generalized Trust, If Anything.pdf},
  journal = {Annual Review of Political Science},
  number = {1}
}

@article{narangDiscoveringArchetypesInterpret,
  title = {Discovering {{Archetypes}} to {{Interpret Evolution}} of {{Individual Behavior}}. ({{arXiv}}:1902.05567v2 [Cs.{{SI}}] {{UPDATED}})},
  author = {Narang, Snigdha Chaturvedi Hari Sundaram Austin Chung Kanika},
  doi = {arXiv:1902.05567v2},
  abstract = {In this paper, we aim to discover archetypical patterns of individual evolution in large social networks. In our work, an archetype comprises of \$\textbackslash textit\{progressive stages\}\$ of distinct behavior. We introduce a novel Gaussian Hidden Markov Model (G-HMM) Cluster to identify archetypes of evolutionary patterns. G-HMMs allow for: near limitless behavioral variation; imposing constraints on how individuals can evolve; different evolutionary rates; and are parsimonious. Our experiments with Academic and StackExchange dataset discover insightful archetypes. We identify four archetypes for researchers: \$\textbackslash textit\{Steady\}\$, \$\textbackslash textit\{Diverse, Evolving and Diffuse\}\$. We observe clear differences in the evolution of male and female researchers within the same archetype. Specifically, women and men differ within an archetype (e.g. Diverse) in how they start, how they transition and the time spent in mid-career. We also found that the differences in grant income are better explained by the differences in archetype than by differences in gender. For StackOverflow, discovered archetypes could be labeled as \$\textbackslash textit\{Experts, Seekers, Enthusiasts, and Facilitators\}\$. We have strong quantitative results with competing baselines for activity prediction and perplexity. For future session prediction, the proposed G-HMM cluster model improves by an average of \$32\textbackslash\%\$ for different Stack Exchanges and \$24\textbackslash\%\$ for Academic dataset. Our model also exhibits lower perplexity than the baselines.},
  journal = {arXiv Physics and Society}
}

@article{narangDiscoveringArchetypesInterpreta,
  title = {Discovering {{Archetypes}} to {{Interpret Evolution}} of {{Individual Behavior}}. ({{arXiv}}:1902.05567v2 [Cs.{{SI}}] {{UPDATED}})},
  author = {Narang, Snigdha Chaturvedi Hari Sundaram Austin Chung Kanika},
  doi = {arXiv:1902.05567v2},
  abstract = {In this paper, we aim to discover archetypical patterns of individual evolution in large social networks. In our work, an archetype comprises of \$\textbackslash textit\{progressive stages\}\$ of distinct behavior. We introduce a novel Gaussian Hidden Markov Model (G-HMM) Cluster to identify archetypes of evolutionary patterns. G-HMMs allow for: near limitless behavioral variation; imposing constraints on how individuals can evolve; different evolutionary rates; and are parsimonious. Our experiments with Academic and StackExchange dataset discover insightful archetypes. We identify four archetypes for researchers: \$\textbackslash textit\{Steady\}\$, \$\textbackslash textit\{Diverse, Evolving and Diffuse\}\$. We observe clear differences in the evolution of male and female researchers within the same archetype. Specifically, women and men differ within an archetype (e.g. Diverse) in how they start, how they transition and the time spent in mid-career. We also found that the differences in grant income are better explained by the differences in archetype than by differences in gender. For StackOverflow, discovered archetypes could be labeled as \$\textbackslash textit\{Experts, Seekers, Enthusiasts, and Facilitators\}\$. We have strong quantitative results with competing baselines for activity prediction and perplexity. For future session prediction, the proposed G-HMM cluster model improves by an average of \$32\textbackslash\%\$ for different Stack Exchanges and \$24\textbackslash\%\$ for Academic dataset. Our model also exhibits lower perplexity than the baselines.},
  journal = {arXiv Physics and Society}
}

@article{nashCulturalTurnSocial2001,
  title = {The `{{Cultural Turn}}' in {{Social Theory}}: {{Towards}} a {{Theory}} of {{Cultural Politics}}},
  shorttitle = {The `{{Cultural Turn}}' in {{Social Theory}}},
  author = {Nash, Kate},
  year = {2001},
  month = feb,
  volume = {35},
  pages = {77--92},
  issn = {00380385},
  doi = {10.1017/S0038038501000050},
  journal = {Sociology},
  number = {1}
}

@article{nasirTrustComputationOnline2020,
  title = {Trust {{Computation}} in {{Online Social Networks Using Co}}-{{Citation}} and {{Transpose Trust Propagation}}},
  author = {Nasir, Safi Ullah and Kim, Tae-Hyung},
  year = {2020},
  doi = {10.1109/ACCESS.2020.2975782},
  abstract = {Evaluating trust and distrust between users in online social networks is an important research problem. To address this problem, we provide a method for estimating continuous trust /distrust value between unconnected users. Our method is based on co-citation and transpose trust propagation. We determine on average how differently two users trust or are trusted by other users, and how differently a user trusts another user from how it is trusted by that user. Using these differences, we estimate four partial trust estimates and compute the final trust value from trustor to trustee as the weighted average of these partial estimates. We propose a basic framework that maximizes accuracy, robustness and coverage and show how we can further improve the accuracy at a lower coverage. We perform experiments on real world trust related networks that show that our proposed method outperforms recent state of the art trust computation methods in terms of accuracy and robustness on commonly used datasets.},
  file = {/home/aleksandar/Zotero/storage/UMH6R7TF/Nasir_Kim_2020_Trust Computation in Online Social Networks Using Co-Citation and Transpose.pdf},
  journal = {IEEE Access}
}

@article{nasrVoterPerceptionsParties2020,
  title = {Voter {{Perceptions}} of {{Parties}}' {{Left}}-{{Right Positions}}: {{The Role}} of {{Party Strategies}}},
  shorttitle = {Voter {{Perceptions}} of {{Parties}}' {{Left}}-{{Right Positions}}},
  author = {Nasr, Mohamed},
  year = {2020},
  publisher = {{Unpublished}},
  doi = {10.13140/RG.2.2.19928.65286},
  abstract = {Left-right semantics help voters simplify the complex political reality as they reduce party views on a variety of issues to a single dimension. Less studied, however, is the question of how voters arrive at parties' left-right positions and how parties can influence voter perceptions. In this article, I demonstrate that parties can shape voter understandings of the content of their left-right position by using three strategies: avoidance, ambivalence, or ambiguity. Specifically, a party may avoid or de-emphasize a given issue, embrace a conflicting position, or becloud its position on the issue in electoral campaigns to induce the voter to place less weight on this issue when perceiving the party's left-right position. To test these hypotheses, the analysis connects voter data from the Comparative Study of Electoral Systems with party data from the Comparative Manifesto Project and the Chapel Hill Expert Survey in 13 West European Countries and finds empirical support for the effectiveness of these strategies.},
  language = {en}
}

@article{navarroJointInferenceMultiple2020,
  title = {Joint {{Inference}} of {{Multiple Graphs}} from {{Matrix Polynomials}}},
  author = {Navarro, Madeline and Wang, Yuhao and Marques, Antonio G. and Uhler, Caroline and Segarra, Santiago},
  year = {2020},
  month = oct,
  abstract = {Inferring graph structure from observations on the nodes is an important and popular network science task. Departing from the more common inference of a single graph and motivated by social and biological networks, we study the problem of jointly inferring multiple graphs from the observation of signals at their nodes (graph signals), which are assumed to be stationary in the sought graphs. From a mathematical point of view, graph stationarity implies that the mapping between the covariance of the signals and the sparse matrix representing the underlying graph is given by a matrix polynomial. A prominent example is that of Markov random fields, where the inverse of the covariance yields the sparse matrix of interest. From a modeling perspective, stationary graph signals can be used to model linear network processes evolving on a set of (not necessarily known) networks. Leveraging that matrix polynomials commute, a convex optimization method along with sufficient conditions that guarantee the recovery of the true graphs are provided when perfect covariance information is available. Particularly important from an empirical viewpoint, we provide high-probability bounds on the recovery error as a function of the number of signals observed and other key problem parameters. Numerical experiments using synthetic and real-world data demonstrate the effectiveness of the proposed method with perfect covariance information as well as its robustness in the noisy regime.},
  archivePrefix = {arXiv},
  eprint = {2010.08120},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Navarro et al/Navarro et al_2020_Joint Inference of Multiple Graphs from Matrix Polynomials.pdf;/home/aleksandar/Zotero/storage/KE98AKD8/2010.html},
  journal = {arXiv:2010.08120 [cs, eess, stat]},
  primaryClass = {cs, eess, stat}
}

@article{nazareNoteReproducibilityChaos2020,
  title = {A {{Note}} on the {{Reproducibility}} of {{Chaos Simulation}}},
  author = {Nazar{\'e}, Thalita E. and Nepomuceno, Erivelton G. and Martins, Samir A. M. and Butusov, Denis N.},
  year = {2020},
  month = aug,
  volume = {22},
  pages = {953},
  issn = {1099-4300},
  doi = {10.3390/e22090953},
  abstract = {An evergreen scientific feature is the ability for scientific works to be reproduced. Since chaotic systems are so hard to understand analytically, numerical simulations assume a key role in their investigation. Such simulations have been considered as reproducible in many works. However, few studies have focused on the effects of the finite precision of computers on the simulation reproducibility of chaotic systems; moreover, code sharing and details on how to reproduce simulation results are not present in many investigations. In this work, a case study of reproducibility is presented in the simulation of a chaotic jerk circuit, using the software LTspice. We also employ the OSF platform to share the project associated with this paper. Tests performed with LTspice XVII on four different computers show the difficulties of simulation reproducibility by this software. We compare these results with experimental data using a normalised root mean square error in order to identify the computer with the highest prediction horizon. We also calculate the entropy of the signals to check differences among computer simulations and the practical experiment. The methodology developed is efficient in identifying the computer with better performance, which allows applying it to other cases in the literature. This investigation is fully described and available on the OSF platform.},
  file = {/home/aleksandar/Zotero/storage/A9A7KIE6/Nazaré et al. - 2020 - A Note on the Reproducibility of Chaos Simulation.pdf},
  journal = {Entropy},
  language = {en},
  number = {9}
}

@article{neathParadoxProblemsTool2019,
  title = {Paradox {{Problems}} as a {{Tool}} for {{Understanding Statistical Reasoning}}},
  author = {Neath, Andrew and Farrar, Nailey},
  year = {2019},
  pages = {4},
  abstract = {Thought experiments in the form of paradox problems are useful for illustrating how our statistical reasoning may be correct, or how it may be flawed, and how our models for behavior in the sciences may be appropriate, or how such models may be incomplete. For example, the Monte Hall problem, the Exchange paradox, the Ellsberg paradox, and transposed conditional paradoxes are all interesting exercises in decision making, quantifying uncertainty, and statistical inference. In this paper, we use the Exchange paradox to illustrate what paradox problems can teach us about the best practices in statistical science.},
  language = {en}
}

@article{nedicGraphTheoreticAnalysisBelief2019,
  title = {Graph-{{Theoretic Analysis}} of {{Belief System Dynamics}} under {{Logic Constraints}}},
  author = {Nedi{\'c}, Angelia and Olshevsky, Alex and Uribe, C{\'e}sar A.},
  year = {2019},
  month = dec,
  volume = {9},
  pages = {8843},
  issn = {2045-2322},
  doi = {10.1038/s41598-019-45076-4},
  file = {/home/aleksandar/Zotero/storage/2HZVSPXA/Nedić et al. - 2019 - Graph-Theoretic Analysis of Belief System Dynamics.pdf},
  journal = {Scientific Reports},
  language = {en},
  number = {1}
}

@article{nemcokTimeGoesSame2020,
  title = {As Time Goes by, the Same Sentiments Apply? {{Stability}} of Voter Satisfaction with Democracy during the Electoral Cycle in 31 Countries},
  shorttitle = {As Time Goes by, the Same Sentiments Apply?},
  author = {Nem{\v c}ok, Miroslav and Wass, Hanna},
  year = {2020},
  month = mar,
  pages = {135406882091246},
  issn = {1354-0688, 1460-3683},
  doi = {10.1177/1354068820912466},
  abstract = {Popular consent is an essential element for success and stability of democracies. Research has repeatedly demonstrated that ``electoral winners'' (i.e. voters casting a ballot for government parties) are more satisfied with democracy than supporters of the opposition parties. However, little is known about the dynamics of satisfaction during the electoral cycle: Do winners become happier and losers even more discontent over time? We approach this question by utilizing an interview date in the European Social Survey (rounds 1\textendash 8) to position individuals within the different stages of electoral cycle. The results based on 199,207 responses from 199 surveys in 31 countries suggest that satisfaction with democracy stays relatively stable during the electoral cycle across various electoral systems if the political development is predictable. However, if actions of the parties are uncertain, namely the alternations of governments tend to be frequent, partial, and opened to all parties, and hence neither winners nor losers know how steady their status is with respect to the political development in the country, their satisfaction tend to fluctuate over time. Therefore, the conclusion reached is the more stable West European democracies have limited generalizability to the low-predictable systems in Central and Eastern Europe.},
  file = {/home/aleksandar/Dropbox/Zotero/Nemčok_Wass/Nemčok_Wass_2020_As time goes by, the same sentiments apply.pdf},
  journal = {Party Politics},
  language = {en}
}

@inproceedings{nepalSTrustTrustModel2011,
  title = {{{STrust}}: {{A Trust Model}} for {{Social Networks}}},
  shorttitle = {{{STrust}}},
  booktitle = {{{2011IEEE}} 10th {{International Conference}} on {{Trust}}, {{Security}} and {{Privacy}} in {{Computing}} and {{Communications}}},
  author = {Nepal, Surya and Sherchan, Wanita and Paris, Cecile},
  year = {2011},
  month = nov,
  pages = {841--846},
  issn = {2324-9013},
  doi = {10.1109/TrustCom.2011.112},
  abstract = {We propose a trust model for social networks with the aim of building trust communities that inspire members to share their experiences, feelings and opinions in an open and honest way without the fear of being judged. The unique feature of our model is that the trust value is derived from the social capital built in the social networks over a period of time. First, we introduce a framework for building trust communities using social trust. We then define an underlying social trust model, called STrust. Finally, we report the current state of the development and the analysis of the proposed trust model.},
  file = {/home/aleksandar/Documents/Zotero/Nepal et al/Nepal et al_2011_STrust.pdf;/home/aleksandar/Zotero/storage/NAWFQXIV/6120905.html}
}

@article{newmanModularityCommunityStructure2006,
  title = {Modularity and Community Structure in Networks},
  author = {Newman, M. E. J.},
  year = {2006},
  month = jun,
  volume = {103},
  pages = {8577--8582},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.0601602103},
  journal = {Proceedings of the National Academy of Sciences},
  language = {en},
  number = {23}
}

@book{newmanNetworksIntroduction2010a,
  ids = {newmanNetworksIntroduction2010},
  title = {Networks: {{An}} Introduction},
  shorttitle = {Networks},
  author = {Newman, M. E. J.},
  year = {2010},
  publisher = {{Oxford University Press}},
  address = {{Oxford}},
  abstract = {"The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks. The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas. Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks"--},
  annotation = {OCLC: ocn456837194},
  isbn = {978-0-19-920665-0},
  lccn = {T57.85 .N523 2010}
}

@article{NewPerspectiveRole2020,
  title = {A New Perspective on the Role of Attitudes in Explaining Travel Behavior: {{A}} Psychological Network Model},
  shorttitle = {A New Perspective on the Role of Attitudes in Explaining Travel Behavior},
  year = {2020},
  month = mar,
  volume = {133},
  pages = {82--94},
  issn = {0965-8564},
  doi = {10.1016/j.tra.2020.01.014},
  abstract = {Psychological factors are generally thought to play an important role in the prediction of individual variations in travel behavior and travel related\ldots},
  journal = {Transportation Research Part A: Policy and Practice},
  language = {en}
}

@article{NewPoliticalSystem,
  title = {A New Political System Model: {{Semi}}\&\#x2010;Parliamentary Government},
  doi = {10.1111/1475-6765.12224},
  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{$>$}Semi-parliamentary government is a distinct executive-legislative system that mirrors             semi-presidentialism. It exists when the legislature is divided into two equally legitimate             parts, only one of which can dismiss the prime minister in a no-confidence vote. This             system has distinct advantages over pure parliamentary and presidential systems: it             establishes a branch-based separation of powers and can balance the `majoritarian'             and `proportional' visions of democracy without concentrating executive power in a             single individual. This article analyses bicameral versions of semi-parliamentary             government in Australia and Japan, and compares empirical patterns of democracy in             the Australian Commonwealth as well as New South Wales to 20 advanced parliamentary             and semi-presidential systems. It discusses new semi-parliamentary designs, some of             which do not require formal bicameralism, and pays special attention to semi-parliamentary             options for democratising the European Union.          {$<$}/p{$>$}},
  journal = {European Journal of Political Research}
}

@article{NewPoliticalSystema,
  title = {A New Political System Model: {{Semi}}\&\#x2010;Parliamentary Government},
  doi = {10.1111/1475-6765.12224},
  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{$>$}Semi-parliamentary government is a distinct executive-legislative system that mirrors             semi-presidentialism. It exists when the legislature is divided into two equally legitimate             parts, only one of which can dismiss the prime minister in a no-confidence vote. This             system has distinct advantages over pure parliamentary and presidential systems: it             establishes a branch-based separation of powers and can balance the `majoritarian'             and `proportional' visions of democracy without concentrating executive power in a             single individual. This article analyses bicameral versions of semi-parliamentary             government in Australia and Japan, and compares empirical patterns of democracy in             the Australian Commonwealth as well as New South Wales to 20 advanced parliamentary             and semi-presidential systems. It discusses new semi-parliamentary designs, some of             which do not require formal bicameralism, and pays special attention to semi-parliamentary             options for democratising the European Union.          {$<$}/p{$>$}},
  journal = {European Journal of Political Research}
}

@article{ngRandomWeightingApproximate2020,
  title = {Random Weighting to Approximate Posterior Inference in {{LASSO}} Regression},
  author = {Ng, Tun Lee and Newton, Michael A.},
  year = {2020},
  month = feb,
  abstract = {We consider a general-purpose approximation approach to Bayesian inference in which repeated optimization of a randomized objective function provides surrogate samples from the joint posterior distribution. In the context of LASSO regression, we repeatedly assign independently-drawn standard-exponential random weights to terms in the objective function, and optimize to obtain the surrogate samples. We establish the asymptotic properties of this me{$\surd$}thod under different regularization parameters {$\lambda$}n. In particular, if {$\lambda$}n = o( n), then the random-weighting (weighted bootstrap) samples are equivalent (up to the first order) to the Bayesian posterior samples. If {$\lambda$}n = O (nc) for some 1/2 {$<$} c {$<$} 1, then these samples achieve conditional model selection consistency. We also establish the asymptotic properties of the random-weighting method when weights are drawn from other distributions, and also if weights are assigned to the LASSO penalty terms.},
  archivePrefix = {arXiv},
  eprint = {2002.02629},
  eprinttype = {arxiv},
  journal = {arXiv:2002.02629 [stat]},
  language = {en},
  primaryClass = {stat}
}

@article{nianInformationPropagationModel2020,
  title = {Information {{Propagation Model}} in {{Hybrid Networks}}},
  author = {Nian, Fuzhong and Diao, Hongyuan},
  year = {2020},
  month = sep,
  abstract = {It is in practice impossible to describe the topology of a real network or its message propagation process using a single dynamic model. To address this issue, we constructed a new hybrid network model based on scale-free (SF), small-world (SW) features that functions as closely as possible to a real network. And the hybrid propagation model is constructed with susceptible-infected-susceptible (SIS), susceptible-infected-recovered (SIR) and susceptible-infected-recovered-susceptible (SIRS) model mixed in arbitrary proportions. The model applies the concepts of blockbuster effect and implicit node edges to reflect explosive spread as a significant characteristic of information propagation. A theoretical analysis and derivation of the new model in which hybrid networks were simulated revealed that the network degree distribution closely follows a power law. Using an improved similarity function to define the degree of closeness to real network cases, the proposed model was shown to be valid and very close to a real network.},
  archivePrefix = {arXiv},
  eprint = {2010.00174},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Nian_Diao/Nian_Diao_2020_Information Propagation Model in Hybrid Networks.pdf;/home/aleksandar/Zotero/storage/S67XAIYV/2010.html},
  journal = {arXiv:2010.00174 [cs]},
  primaryClass = {cs}
}

@article{nicewanderPerspectiveMathematicalPsychometric2019,
  ids = {nicewanderPerspectiveMathematicalPsychometric,nicewanderPerspectiveMathematicalPsychometrica,nicewanderPerspectiveMathematicalPsychometricb},
  title = {A {{Perspective}} on the {{Mathematical}} and {{Psychometric Aspects}} of {{Factor Indeterminacy}}},
  author = {Nicewander, W. Alan},
  year = {2019},
  month = nov,
  volume = {0},
  pages = {1--14},
  issn = {0027-3171},
  doi = {10.1080/00273171.2019.1684872},
  abstract = {It is generally known that the factors in the common factor model (CFM) cannot be solved for uniquely even if the factor model fits perfectly and the factor loadings are known. This indeterminacy of the factor variables (often referred to as `factor scores') stems from the fact that the CFM is a set of underdetermined linear equations that has more unknowns than equations\textemdash a situation which produces an infinity of alternative solutions. In the first section of this inquiry, factor indeterminacy for all factors, common and unique, is examined in the context of The Theory of Generalized Inverses (TGI). Casting factor indeterminacy in the context of TGI provides some simpler results than older approaches. It is shown, for example, that essentially all statistical properties of the infinity of solutions are summarized in the elements of a single, idempotent matrix\textemdash symbolized here as H. In the final section of this article, a psychometric view of indeterminacy is presented in which it is argued that the two causes of indeterminacy are low reliabilities and low communalities of the observed variables. It is shown that the diagonal elements of the matrix H are reliability coefficients; therefore, the Spearman-Brown equation can be brought to bear on how much indeterminacy can be reduced by repeated sampling from an Infinite Behavior Domain (IBD). A brief discussion is presented on the effects of factor indeterminacy in IRT models.},
  journal = {Multivariate Behavioral Research},
  number = {0},
  pmid = {31709826}
}

@article{nicolaouMissingLinksSource2020,
  title = {Missing Links as a Source of Seemingly Variable Constants in Complex Reaction Networks},
  author = {Nicolaou, Zachary G. and Motter, Adilson E.},
  year = {2020},
  month = oct,
  volume = {2},
  pages = {043135},
  issn = {2643-1564},
  doi = {10.1103/PhysRevResearch.2.043135},
  file = {/home/aleksandar/Zotero/storage/I8FDMUZ7/Nicolaou and Motter - 2020 - Missing links as a source of seemingly variable co.pdf},
  journal = {Physical Review Research},
  language = {en},
  number = {4}
}

@article{nicolaouMissingLinksSource2020a,
  title = {Missing Links as a Source of Seemingly Variable Constants in Complex Reaction Networks},
  author = {Nicolaou, Zachary G},
  year = {2020},
  pages = {10},
  file = {/home/aleksandar/Zotero/storage/67HAX2T8/Nicolaou - 2020 - Missing links as a source of seemingly variable co.pdf},
  language = {en}
}

@article{niuBayesianGraphSelection,
  title = {Bayesian {{Graph Selection Consistency For Decomposable Graphs}}.},
  author = {Niu, Yabo and Pati, Debdeep and Mallick, Bani},
  doi = {arXiv:1901.04134v1},
  abstract = {{$<$}p{$>$}Gaussian graphical models are a popular tool to learn the dependence structure in the form of a graph among variables of interest. Bayesian methods have gained in popularity in the last two decades due to their ability to simultaneously learn the covariance and the graph and characterize uncertainty in the selection. For scalability of the Markov chain Monte Carlo algorithms, decomposability is commonly imposed on the graph space. A wide variety of graphical conjugate priors are proposed jointly on the covariance matrix and the graph with improved algorithms to search along the space of decomposable graphs, rendering the methods extremely popular in the context of multivariate dependence modeling. \{\textbackslash it An open problem\} in Bayesian decomposable structure learning is whether the posterior distribution is able to select the true graph asymptotically when the dimension of the variables increases with the sample size. In this article, we explore specific conditions on the true precision matrix and the graph which results in an affirmative answer to this question using a commonly used hyper-inverse Wishart prior on the covariance matrix and a suitable complexity prior on the graph space. In absence of structural sparsity assumptions, our strong selection consistency holds in a high dimensional setting where \$p = O(n\^\{\textbackslash alpha\})\$ for \$\textbackslash alpha \< 1/3\$. In addition, we show when the likelihood is misspecified, i.e. when the true graph is non-decomposable, the posterior distribution on the graph concentrates on a set of graphs that are minimal triangulations of the true graph. {$<$}/p{$>$}},
  journal = {arXiv Statistics Theory}
}

@article{niuBayesianGraphSelectiona,
  title = {Bayesian {{Graph Selection Consistency For Decomposable Graphs}}.},
  author = {Niu, Yabo and Pati, Debdeep and Mallick, Bani},
  doi = {arXiv:1901.04134v1},
  abstract = {{$<$}p{$>$}Gaussian graphical models are a popular tool to learn the dependence structure in the form of a graph among variables of interest. Bayesian methods have gained in popularity in the last two decades due to their ability to simultaneously learn the covariance and the graph and characterize uncertainty in the selection. For scalability of the Markov chain Monte Carlo algorithms, decomposability is commonly imposed on the graph space. A wide variety of graphical conjugate priors are proposed jointly on the covariance matrix and the graph with improved algorithms to search along the space of decomposable graphs, rendering the methods extremely popular in the context of multivariate dependence modeling. \{\textbackslash it An open problem\} in Bayesian decomposable structure learning is whether the posterior distribution is able to select the true graph asymptotically when the dimension of the variables increases with the sample size. In this article, we explore specific conditions on the true precision matrix and the graph which results in an affirmative answer to this question using a commonly used hyper-inverse Wishart prior on the covariance matrix and a suitable complexity prior on the graph space. In absence of structural sparsity assumptions, our strong selection consistency holds in a high dimensional setting where \$p = O(n\^\{\textbackslash alpha\})\$ for \$\textbackslash alpha \< 1/3\$. In addition, we show when the likelihood is misspecified, i.e. when the true graph is non-decomposable, the posterior distribution on the graph concentrates on a set of graphs that are minimal triangulations of the true graph. {$<$}/p{$>$}},
  journal = {arXiv Statistics Theory}
}

@article{noorazarClassicalModernOpinion2020,
  title = {From {{Classical}} to {{Modern Opinion Dynamics}}},
  author = {Noorazar, Hossein and Vixie, K. and Talebanpour, Arghavan and Hu, Yunfeng},
  year = {2020},
  doi = {10.1142/S0129183120501016},
  abstract = {In this age of Facebook, Instagram and Twitter, there is rapidly growing interest in understanding network-enabled opinion dynamics in large groups of autonomous agents. The phenomena of opinion polarization, the spread of propaganda and fake news, and the manipulation of sentiment are of interest to large numbers of organizations and people, some of whom are resource rich. Whether it is the more nefarious players such as foreign governments that are attempting to sway elections or large corporations that are trying to bend sentiment -- often quite surreptitiously, or it is more open and above board, like researchers that want to spread the news of some finding or some business interest that wants to make a large group of people aware of genuinely helpful innovations that they are marketing, what is at stake is often significant. In this paper we review many of the classical, and some of the new, social interaction models aimed at understanding opinion dynamics. While the first papers studying opinion dynamics appeared over 60 years ago, there is still a great deal of room for innovation and exploration. We believe that the political climate and the extraordinary (even unprecedented) events in the sphere of politics in the last few years will inspire new interest and new ideas. It is our aim to help those interested researchers understand what has already been explored in a significant portion of the field of opinion dynamics. We believe that in doing this, it will become clear that there is still much to be done.},
  file = {/home/aleksandar/Documents/Zotero/Noorazar et al/Noorazar et al_2020_From Classical to Modern Opinion Dynamics.pdf}
}

@article{noorazarRecentAdvancesOpinion2020,
  title = {Recent Advances in Opinion Propagation Dynamics: {{A}} 2020 {{Survey}}},
  shorttitle = {Recent Advances in Opinion Propagation Dynamics},
  author = {Noorazar, Hossein},
  year = {2020},
  month = jun,
  volume = {135},
  pages = {521},
  issn = {2190-5444},
  doi = {10.1140/epjp/s13360-020-00541-2},
  abstract = {Opinion dynamics have attracted the interest of researchers from different fields. Local interactions among individuals create interesting dynamics for the system as a whole. Such dynamics are important from a variety of perspectives. Group decision making, successful marketing, and constructing networks (in which consensus can be reached or prevented) are a few examples of existing or potential applications. The invention of the Internet has made the opinion fusion faster, unilateral, and on a whole different scale. Spread of fake news, propaganda, and election interferences have made it clear there is an essential need to know more about these dynamics. The emergence of new ideas in the field has accelerated over the last few years. In the first quarter of 2020, at least 50 research papers have emerged, either peer-reviewed and published or on pre-print outlets such as arXiv. In this paper, we summarize these ground-breaking ideas and their fascinating extensions and introduce newly surfaced concepts.},
  archivePrefix = {arXiv},
  eprint = {2004.05286},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Noorazar/Noorazar_2020_Recent advances in opinion propagation dynamics.pdf;/home/aleksandar/Dropbox/Zotero/Noorazar/Noorazar_2020_Recent advances in opinion propagation dynamics2.pdf;/home/aleksandar/Zotero/storage/XB6DJXEJ/2004.html},
  journal = {The European Physical Journal Plus},
  number = {6}
}

@article{noorazarRecentAdvancesOpinion2020a,
  title = {Recent Advances in Opinion Propagation Dynamics: A 2020 Survey},
  shorttitle = {Recent Advances in Opinion Propagation Dynamics},
  author = {Noorazar, Hossein},
  year = {2020},
  doi = {10.1140/epjp/s13360-020-00541-2},
  abstract = {Opinion dynamics have attracted the interest of researchers from different fields. Local interactions among individuals create interesting dynamics for the system as a whole. Such dynamics are important from a variety of perspectives. Group decision making, successful marketing, and constructing networks (in which consensus can be reached or prevented) are a few examples of existing or potential applications. The invention of the Internet has made the opinion fusion faster, unilateral, and on a whole different scale. Spread of fake news, propaganda, and election interferences have made it clear there is an essential need to know more about these dynamics. The emergence of new ideas in the field has accelerated over the last few years. In the first quarter of 2020, at least 50 research papers have emerged, either peer-reviewed and published or on preprint outlets such as arXiv. In this paper, we summarize these ground-breaking ideas and their fascinating extensions and introduce newly surfaced concepts.},
  file = {/home/aleksandar/Documents/Zotero/Noorazar/Noorazar_2020_Recent advances in opinion propagation dynamics.pdf},
  journal = {ArXiv}
}

@techreport{norgaardKernelIntegrationGraphical2020,
  title = {Kernel Integration by {{Graphical LASSO}}},
  author = {N{\o}rgaard, Sarah Kristine and {Linder-Steinlein}, Kristoffer and Eliasen, Anders Ulrik and Stokholm, Jakob and Chawez, Bo L. and B{\o}nnelykke, Klaus and Bisgaard, Hans and Smilde, Age K. and Rasmussen, Morten A.},
  year = {2020},
  month = mar,
  institution = {{Bioinformatics}},
  doi = {10.1101/2020.03.11.986968},
  abstract = {Integration of unstructured and very diverse data is often required for a deeper understanding of complex biological systems. In order to uncover communalities between heterogeneous data, the data is often harmonized by constructing a kernel and numerical integration is performed. In this study we propose a method for data integration in the framework of an undirected graphical model, where the nodes represent individual data sources of varying nature in terms of complexity and underlying distribution, and where the edges represent the partial correlation between two blocks of data. We propose a modified GLASSO for estimation of the graph, with a combination of cross-validation and extended Bayes Information Criterion for sparsity tuning. Furthermore, hierarchical clustering on the weighted consensus kernels from a fixed network is used to partitioning the samples into different classes. Simulations show increasing ability to uncover true edges with increasing sample size and             signal to noise             . Likewise, identification of non existing edges towards disconnected nodes is feasible. The framework is demonstrated for integration of longitudinal symptom burden data from the 2nd and 3rd year of life with 21 diseases precursors as well as the development of asthma and eczema at the age of 6 years from 403 children from the COPSAC2010 mother-child cohort, suggesting that maternal predisposition as well as being born preterm indirectly lead to higher risk of asthma via increased respiratory symptom burden.},
  file = {/home/aleksandar/Dropbox/Zotero/Nørgaard et al/Nørgaard et al_2020_Kernel integration by Graphical LASSO.pdf},
  language = {en},
  type = {Preprint}
}

@book{norrisCulturalBacklashTrump2019,
  title = {Cultural {{Backlash}}: {{Trump}}, {{Brexit}}, and {{Authoritarian Populism}}},
  shorttitle = {Cultural {{Backlash}}},
  author = {Norris, Pippa and Inglehart, Ronald},
  year = {2019},
  month = feb,
  edition = {First},
  publisher = {{Cambridge University Press}},
  doi = {10.1017/9781108595841},
  file = {/home/aleksandar/Zotero/storage/E28EDUX5/Norris and Inglehart - 2019 - Cultural Backlash Trump, Brexit, and Authoritaria.pdf},
  isbn = {978-1-108-59584-1 978-1-108-42607-7 978-1-108-44442-2},
  language = {en}
}

@article{norrisMeasuringPopulismWorldwide,
  title = {Measuring {{Populism Worldwide}}},
  author = {Norris, Pippa},
  pages = {40},
  abstract = {Synopsis: Populism studies have rapidly burgeoned but nevertheless systematic cross-national evidence about this phenomenon has lagged far behind. How can populism be measured in ways which are consistent, valid, and reliable? To address this issue, Part I outlines the minimalist concept of populism used in the study. Part II summarizes the pros and cons of previous attempts at gauging and classifying party ideological values and issue positions in general, as well as recent studies seeking to classify populists as a distinct party family. Part III describes the research design employed to construct the Global Party Survey, replicating the methods of previous expert surveys but expanding coverage worldwide and including innovative measures of populist rhetoric. The new dataset, drawing upon estimates from 1,861 experts, covers 1,043 political parties in 163 countries around the globe (see www.GlobalPartySurvey.org). Part IV presents key results and a series of robustness tests confirming that the new estimates of ideological values and populist parties are consistently correlated with previous measures. The conclusion in Part V summarizes the results and considers the potential uses of the dataset for understanding populism as a global phenomenon.},
  file = {/home/aleksandar/Zotero/storage/LIGXNLGA/Norris - Measuring Populism Worldwide.pdf},
  language = {en}
}

@article{novelliInferringNetworkProperties2020,
  title = {Inferring Network Properties from Time Series via Transfer Entropy and Mutual Information: Validation of Bivariate versus Multivariate Approaches},
  shorttitle = {Inferring Network Properties from Time Series via Transfer Entropy and Mutual Information},
  author = {Novelli, Leonardo and Lizier, Joseph T.},
  year = {2020},
  month = jul,
  abstract = {Functional and effective networks inferred from time series are at the core of network neuroscience. Since it is common practice to compare network properties between patients and controls, it is crucial for inferred network models to reflect key underlying structural properties. However, even a few spurious links severely distort the shortest-path length and derived measures including the small-world coefficient, providing misleading insights into the macroscopic topology of the network. This poses a challenge for functional connectomes based on correlation, whose transitivity necessarily induce numerous false positives. We study how false positives bias the properties of the networks inferred by bivariate and multivariate algorithms. Mutual information, bivariate transfer entropy, and multivariate transfer entropy are respectively used for inferring functional, directed-functional, and effective networks. The validation is performed on synthetic ground truth networks with 100--200 nodes and various topologies (regular lattice, small-world, random, scale-free, modular), as well as on a real macaque connectome. The time series of node activity are simulated via autoregressive dynamics. We find that multivariate transfer entropy captures key properties of all network structures for longer time series. Bivariate methods can achieve higher recall (sensitivity) for shorter time series; however, as available data increases, they are unable to control false positives (lower specificity). This leads to overestimated clustering, small-world, and rich-club coefficients, underestimated shortest path lengths and hub centrality, and fattened degree distribution tails. Caution should therefore be used when interpreting network properties of functional connectomes obtained via correlation or pairwise statistical dependence measures, rather than more holistic (yet data-hungry) multivariate models.},
  archivePrefix = {arXiv},
  eprint = {2007.07500},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/UXMU28ZI/Novelli and Lizier - 2020 - Inferring network properties from time series via .pdf},
  journal = {arXiv:2007.07500 [physics, q-bio]},
  language = {en},
  primaryClass = {physics, q-bio}
}

@article{noventaGeneralizationLocalIndependence,
  ids = {noventaGeneralizationLocalIndependencea},
  title = {On a {{Generalization}} of {{Local Independence}} in {{Item Response Theory Based}} on {{Knowledge Space Theory}}},
  author = {Noventa, Stefano and Spoto, Andrea and Heller, J{\"u}rgen and Kelava, Augustin},
  doi = {10.1007/s11336-018-9645-6},
  abstract = {{$<$}h3 class="a-plus-plus"{$>$}Abstract{$<$}/h3{$>$}                   {$<$}p class="a-plus-plus"{$>$}Knowledge space theory (KST) structures are introduced within item response theory (IRT) as a possible way to model local dependence between items. The aim of this paper is threefold: firstly, to generalize the usual characterization of local independence without introducing new parameters; secondly, to merge the information provided by the IRT and KST perspectives; and thirdly, to contribute to the literature that bridges continuous and discrete theories of assessment. In detail, connections are established between the KST simple learning model (SLM) and the IRT General Graded Response Model, and between the KST Basic Local Independence Model and IRT models in general. As a consequence, local independence is generalized to account for the existence of prerequisite relations between the items, IRT models become a subset of KST models, IRT likelihood functions can be generalized to broader families, and the issues of local dependence and dimensionality are partially disentangled. Models are discussed for both dichotomous and polytomous items and conclusions are drawn on their interpretation. Considerations on possible consequences in terms of model identifiability and estimation procedures are also provided.{$<$}/p{$>$}},
  journal = {Psychometrika}
}

@article{nowakNonlinearSocietalChange2019,
  title = {Nonlinear Societal Change: {{The}} Perspective of Dynamical Systems},
  shorttitle = {Nonlinear Societal Change},
  author = {Nowak, Andrzej and Vallacher, Robin R.},
  year = {2019},
  volume = {58},
  pages = {105--128},
  issn = {2044-8309},
  doi = {10.1111/bjso.12271},
  abstract = {Although rapid social change reflects each society's unique combination of myriad social, historical, political, and economic factors, we argue that the defining features of such change can be understood with recourse to the dynamic processes inherent in complex systems. Accordingly, we present a formal model that describes, in minimalist terms, the dynamics associated with rapid societal transitions in a society's norms and attitudes\textemdash and to the potential for rapid reversals of these transitions. The model predicts that societies in the midst of rapid change are characterized by dual realities corresponding to the new and the old, so that models focusing only on changes in the central tendency of a societal attitude provide a misleading account of rapid social change. This model is implemented in computer simulations and validated with empirical data concerning the transition in Eastern Europe from communism to democracy and a free market economy in the late 1980s.},
  annotation = {\_eprint: https://bpspsychub.onlinelibrary.wiley.com/doi/pdf/10.1111/bjso.12271},
  copyright = {\textcopyright{} 2018 The British Psychological Society},
  file = {/home/aleksandar/Zotero/storage/CJGBYG9Q/bjso.html;/home/aleksandar/Zotero/storage/RYGTMJTB/bjso.html},
  journal = {British Journal of Social Psychology},
  keywords = {agent-based modelling,computational models,dynamical systems,rapid societal change,social change,social influence},
  language = {en},
  number = {1}
}

@article{nsourHotGetRicherNetworkGrowth2020,
  title = {Hot-{{Get}}-{{Richer Network Growth Model}}},
  author = {Nsour, Faisal and Sayama, Hiroki},
  year = {2020},
  month = oct,
  abstract = {Under preferential attachment (PA) network growth models late arrivals are at a disadvantage with regard to their final degrees. Previous extensions of PA have addressed this deficiency by either adding the notion of node fitness to PA, usually drawn from some fitness score distributions, or by using fitness alone to control attachment. Here we introduce a new dynamical approach to address late arrivals by adding a recent-degree-change bias to PA so that nodes with higher relative degree change in temporal proximity to an arriving node get an attachment probability boost. In other words, if PA describes a rich-get-richer mechanism, and fitness-based approaches describe good-get-richer mechanisms, then our model can be characterized as a hot-get-richer mechanism, where hotness is determined by the rate of degree change over some recent past. The proposed model produces much later high-ranking nodes than the PA model and, under certain parameters, produces networks with structure similar to PA networks.},
  archivePrefix = {arXiv},
  eprint = {2010.08659},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Nsour_Sayama/Nsour_Sayama_2020_Hot-Get-Richer Network Growth Model.pdf;/home/aleksandar/Zotero/storage/36V77A7C/2010.html},
  journal = {arXiv:2010.08659 [cs]},
  primaryClass = {cs}
}

@article{nunez-barriopedroHappinessPerceptionSpain2019,
  title = {Happiness Perception in {{Spain}}, a {{SEM}} Approach to Evidence from the Sociological Research Center},
  author = {{N{\'u}{\~n}ez-Barriopedro}, Estela and {Ravina-Ripoll}, Rafael and {Ahumada-Tello}, Eduardo},
  year = {2019},
  month = dec,
  issn = {1573-7845},
  doi = {10.1007/s11135-019-00955-w},
  abstract = {In the current study, we examined the relationship between perceived person happiness and factors that influence this perception, also, is inferred that life satisfaction is influence by happiness. Among 2494 Spaniards individuals of both sexes, we found that these individuals valued political situation, economic situation and socio-demographic characteristics to have a strong association in that order, with happiness and that this last construct is a fundamental factor to life satisfaction. The importance of perception is validated using a structural equation model that evaluates relationships and validity on the constructs in question. Collinearity statistics, average variance extracted, and an estimated partial least square regression model are evaluated to confirm independent meaning, correct construct measure and endogenous variable explanation by the predictive constructs. Results indicate that the level of happiness in Spaniards is most influenced by political perception. Theoretical and practical implications of these findings are discussed, and it is proposed to continue this study in a non-developed country.},
  journal = {Quality \& Quantity},
  language = {en}
}

@article{nussbaumIsingModelsLatent,
  title = {Ising {{Models}} with {{Latent Conditional Gaussian Variables}}.},
  author = {Nussbaum, Frank and Giesen, Joachim},
  doi = {arXiv:1901.09712v1},
  abstract = {{$<$}p{$>$}Ising models describe the joint probability distribution of a vector of binary feature variables. Typically, not all the variables interact with each other and one is interested in learning the presumably sparse network structure of the interacting variables. However, in the presence of latent variables, the conventional method of learning a sparse model might fail. This is because the latent variables induce indirect interactions of the observed variables. In the case of only a few latent conditional Gaussian variables these spurious interactions contribute an additional low-rank component to the interaction parameters of the observed Ising model. Therefore, we propose to learn a sparse + low-rank decomposition of the parameters of an Ising model using a convex regularized likelihood problem. We show that the same problem can be obtained as the dual of a maximum-entropy problem with a new type of relaxation, where the sample means collectively need to match the expected values only up to a given tolerance. The solution to the convex optimization problem has consistency properties in the high-dimensional setting, where the number of observed binary variables and the number of latent conditional Gaussian variables are allowed to grow with the number of training samples. {$<$}/p{$>$}},
  journal = {arXiv Machine Learning (Statistics)}
}

@article{nussbaumIsingModelsLatenta,
  title = {Ising {{Models}} with {{Latent Conditional Gaussian Variables}}.},
  author = {Nussbaum, Frank and Giesen, Joachim},
  doi = {arXiv:1901.09712v1},
  abstract = {{$<$}p{$>$}Ising models describe the joint probability distribution of a vector of binary feature variables. Typically, not all the variables interact with each other and one is interested in learning the presumably sparse network structure of the interacting variables. However, in the presence of latent variables, the conventional method of learning a sparse model might fail. This is because the latent variables induce indirect interactions of the observed variables. In the case of only a few latent conditional Gaussian variables these spurious interactions contribute an additional low-rank component to the interaction parameters of the observed Ising model. Therefore, we propose to learn a sparse + low-rank decomposition of the parameters of an Ising model using a convex regularized likelihood problem. We show that the same problem can be obtained as the dual of a maximum-entropy problem with a new type of relaxation, where the sample means collectively need to match the expected values only up to a given tolerance. The solution to the convex optimization problem has consistency properties in the high-dimensional setting, where the number of observed binary variables and the number of latent conditional Gaussian variables are allowed to grow with the number of training samples. {$<$}/p{$>$}},
  journal = {arXiv Machine Learning (Statistics)}
}

@article{nylundDecidingNumberClasses2007,
  title = {Deciding on the {{Number}} of {{Classes}} in {{Latent Class Analysis}} and {{Growth Mixture Modeling}}: {{A Monte Carlo Simulation Study}}},
  shorttitle = {Deciding on the {{Number}} of {{Classes}} in {{Latent Class Analysis}} and {{Growth Mixture Modeling}}},
  author = {Nylund, Karen L. and Asparouhov, Tihomir and Muth{\'e}n, Bengt O.},
  year = {2007},
  month = oct,
  volume = {14},
  pages = {535--569},
  issn = {1070-5511, 1532-8007},
  doi = {10.1080/10705510701575396},
  journal = {Structural Equation Modeling: A Multidisciplinary Journal},
  language = {en},
  number = {4}
}

@article{oberskiEvaluatingSensitivityParameters2014,
  title = {Evaluating {{Sensitivity}} of {{Parameters}} of {{Interest}} to {{Measurement Invariance}} in {{Latent Variable Models}}},
  author = {Oberski, Daniel L.},
  year = {2014},
  volume = {22},
  pages = {45--60},
  issn = {1047-1987, 1476-4989},
  doi = {10.1093/pan/mpt014},
  abstract = {Latent variable models can only be compared across groups when these groups exhibit measurement equivalence or ``invariance,'' since otherwise substantive differences may be confounded with measurement differences. This article suggests examining directly whether measurement differences present could confound substantive analyses, by examining the expected parameter change (EPC)-interest. The EPC-interest approximates the change in parameters of interest that can be expected when freeing cross-group invariance restrictions. Monte Carlo simulations suggest that the EPC-interest approximates these changes well. Three empirical applications show that the EPC-interest can help avoid two undesirable situations: first, it can prevent unnecessarily concluding that groups are incomparable, and second, it alerts the user when comparisons of interest may still be invalidated even when the invariance model appears to fit the data. R code and data for the examples discussed in this article are provided in the electronic appendix (               http://hdl.handle.net/1902.1/21816               ).},
  file = {/home/aleksandar/Dropbox/Zotero/Oberski/Oberski_2014_Evaluating Sensitivity of Parameters of Interest to Measurement Invariance in.pdf},
  journal = {Political Analysis},
  language = {en},
  number = {1}
}

@article{odellLearningContinuousOccupancy2019,
  title = {Learning {{Continuous Occupancy Maps}} with the {{Ising Process Model}}},
  author = {O'Dell, Nicholas and Renton, Christopher and Wills, Adrian},
  year = {2019},
  month = oct,
  abstract = {We present a new method of learning a continuous occupancy field for use in robot navigation. Occupancy grid maps, or variants of, are possibly the most widely used and accepted method of building a map of a robot's environment. Various methods have been developed to learn continuous occupancy maps and have successfully resolved many of the shortcomings of grid mapping, namely, priori discretisation and spatial correlation. However, most methods for producing a continuous occupancy field remain computationally expensive or heuristic in nature. Our method explores a generalisation of the so-called Ising model as a suitable candidate for modelling an occupancy field. We also present a unique kernel for use within our method that models range measurements. The method is quite attractive as it requires only a small number of hyperparameters to be trained, and is computationally efficient. The small number of hyperparameters can be quickly learned by maximising a pseudo likelihood. The technique is demonstrated on both a small simulated indoor environment with known ground truth as well as large indoor and outdoor areas, using two common real data sets.},
  archivePrefix = {arXiv},
  eprint = {1910.08225},
  eprinttype = {arxiv},
  journal = {arXiv:1910.08225 [cs, stat]},
  language = {en},
  primaryClass = {cs, stat}
}

@article{okanoInfluenceSocialMedia,
  ids = {okanoInfluenceSocialMediaa},
  title = {The {{Influence}} of {{Social Media Writing}} on {{Online Search Behavior}} for {{Seasonal Events}}: {{The Sociophysics Approach}}.},
  author = {Okano, Nozomi and Higashi, Masaru and Ishii, Akira},
  doi = {arXiv:1901.00076v1},
  abstract = {{$<$}p{$>$}Using seasonal topics as the study subject, in this study, we focus on the timing gap between social media writing and online search behavior. To conduct our analysis, we used the mathematical model of search behavior, comprising the sociophysics approach. The seasonal topics selected were St.Valentine's Day, Halloween and New Year countdown. We also picked up the event like Christmas and Halloween. We analyzed the influence of blogs and Twitter on search behavior and found a deviation of interest in terms of timing. We also analyzed Japanese seasonal event of eating Eho-maki in February 3 and eels at the day of the ox in midsummer. {$<$}/p{$>$}},
  journal = {arXiv Computer Science}
}

@inproceedings{okanoTwoComponentOpinionDynamics2020,
  title = {Two-{{Component Opinion Dynamics Theory}} of {{Official Stance}} and {{Real Opinion Including Self}}-{{Interaction}}},
  booktitle = {Intelligent {{Decision Technologies}}},
  author = {Okano, Nozomi and Ohira, Yuki and Ishii, Akira},
  editor = {Czarnowski, Ireneusz and Howlett, Robert J. and Jain, Lakhmi C.},
  year = {2020},
  pages = {461--470},
  publisher = {{Springer}},
  address = {{Singapore}},
  doi = {10.1007/978-981-15-5925-9_39},
  abstract = {We extend the theory of opinion dynamics, which introduces trust and distrust in human relationships in society, to multiple components. The theory is made up of N components, and in particular, here, two components are treated. In this paper, we show the calculation for real opinion and official stance as the two components of opinions.},
  isbn = {9789811559259},
  language = {en},
  series = {Smart {{Innovation}}, {{Systems}} and {{Technologies}}}
}

@article{okolikjTherePartisanBias2020,
  title = {Is There a Partisan Bias in the Perception of the State of the Economy? {{A}} Comparative Investigation of {{European}} Countries, 2002\textendash 2016},
  shorttitle = {Is There a Partisan Bias in the Perception of the State of the Economy?},
  author = {Okolikj, Martin and Hooghe, Marc},
  year = {2020},
  month = may,
  pages = {0192512120915907},
  publisher = {{SAGE Publications Ltd}},
  issn = {0192-5121},
  doi = {10.1177/0192512120915907},
  abstract = {The literature on economic voting starts from the assumptions that citizens have a sufficiently high level of knowledge about their country's economic situation, and that they vote according to their perception of the state of the economy. However, these assumptions have been challenged as economic perceptions could be plagued by partisan bias. We use the comparative dataset of the European Social Survey to investigate partisan bias in the perception of economic performance. Firstly, we observe that the economic perceptions of both supporters and opponents of governing parties are strongly related to real-life economic indicators such as gross domestic product growth and unemployment levels. Secondly, we find that shifts in economic performance (growth and unemployment) are strongly associated with similar changes in economic perceptions among both supporters of governing parties and opposition parties. There is, however, a significant but limited partisan bias in economic perceptions in countries with high levels of unemployment.},
  journal = {International Political Science Review},
  language = {en}
}

@article{olatunjiDisgustScaleItem2007,
  title = {The {{Disgust Scale}}: {{Item}} Analysis, Factor Structure, and Suggestions for Refinement},
  shorttitle = {The {{Disgust Scale}}},
  author = {Olatunji, Bunmi O. and Williams, Nathan L. and Tolin, David F. and Abramowitz, Jonathan S. and Sawchuk, Craig N. and Lohr, Jeffrey M. and Elwood, Lisa S.},
  year = {2007},
  volume = {19},
  pages = {281--297},
  issn = {1939-134X(Electronic),1040-3590(Print)},
  doi = {10.1037/1040-3590.19.3.281},
  abstract = {In the 4 studies presented (N = 1,939), a converging set of analyses was conducted to evaluate the item adequacy, factor structure, reliability, and validity of the Disgust Scale (DS; J. Haidt, C. McCauley, \& P. Rozin, 1994). The results suggest that 7 items (i.e., Items 2, 7, 8, 21, 23, 24, and 25) should be considered for removal from the DS. Secondary to removing the items, exploratory and confirmatory factor analyses revealed that the DS taps 3 dimensions of disgust: Core Disgust, Animal Reminder Disgust, and Contamination-Based Disgust. Women scored higher than men on the 3 disgust dimensions. Structural modeling provided support for the specificity of the 3-factor model, as Core Disgust and Contamination-Based Disgust were significantly predictive of obsessive- compulsive disorder (OCD) concerns, whereas Animal Reminder Disgust was not. Results from a clinical sample indicated that patients with OCD washing concerns scored significantly higher than patients with OCD without washing concerns on both Core Disgust and Contamination-Based Disgust, but not on Animal Reminder Disgust. These findings are discussed in the context of the refinement of the DS to promote a more psychometrically sound assessment of disgust sensitivity. (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
  file = {/home/aleksandar/Zotero/storage/XJI22XTT/2007-12847-003.html},
  journal = {Psychological Assessment},
  number = {3}
}

@article{olsonDictatorshipDemocracyDevelopment1993,
  title = {Dictatorship, {{Democracy}}, and {{Development}}},
  author = {Olson, Mancur},
  year = {1993},
  month = sep,
  volume = {87},
  pages = {567--576},
  issn = {0003-0554, 1537-5943},
  doi = {10.2307/2938736},
  abstract = {Under anarchy, uncoordinated competitive theft by ``roving bandits'' destroys the incentive to invest and produce, leaving little for either the population or the bandits. Both can be better off if a bandit sets himself up as a dictator\textemdash a ``stationary bandit'' who monopolizes and rationalizes theft in the form of taxes. A secure autocrat has an encompassing interest in his domain that leads him to provide a peaceful order and other public goods that increase productivity. Whenever an autocrat expects a brief tenure, it pays him to confiscate those assets whose tax yield over his tenure is less than their total value. This incentive plus the inherent uncertainty of succession in dictatorships imply that autocracies will rarely have good economic performance for more than a generation. The conditions necessary for a lasting democracy are the same necessary for the security of property and contract rights that generates economic growth.},
  journal = {American Political Science Review},
  language = {en},
  number = {3}
}

@article{olsonReligionPublicOpinion2006,
  title = {Religion and {{Public Opinion}} about {{Same}}-{{Sex Marriage}}*},
  author = {Olson, Laura R. and Cadge, Wendy and Harrison, James T.},
  year = {2006},
  month = jun,
  volume = {87},
  pages = {340--360},
  issn = {0038-4941, 1540-6237},
  doi = {10.1111/j.1540-6237.2006.00384.x},
  journal = {Social Science Quarterly},
  language = {en},
  number = {2}
}

@article{olthofComplexityPsychologicalSelfRatings,
  title = {Complexity in {{Psychological Self}}-{{Ratings}}: {{Implications}} for Research and Practice},
  author = {Olthof, Merlijn and Hasselman, Fred and {Lichtwarck-Aschoff}, Anna},
  pages = {49},
  abstract = {Background: Psychopathology research is changing focus from group-based `disease models' to a personalized approach inspired by complex systems theories. This approach, which has already produced novel and valuable insights into the complex nature of psychopathology, often relies on repeated self-ratings of individual patients. So far it has been unknown whether such self-ratings, the presumed observables of the individual patient as a complex system, actually display complex dynamics. We examine this basic assumption of a complex systems approach to psychopathology by testing repeated self-ratings for three markers of complexity: memory, the presence of (time-varying) short- and long-range temporal correlations, regime shifts, transitions between different dynamic regimes, and, sensitive dependence on initial conditions, also known as the `butterfly effect', the divergence of initially similar trajectories. Methods: We analysed repeated self-ratings (1,476 time points) from a single patient for the three markers of complexity using Bartels rank test, (partial) autocorrelation functions, timevarying autoregression, a non-stationarity test, change point analysis and the Sugihara-May algorithm. Results: Self-ratings concerning psychological states (e.g., the item `I feel down') exhibited all complexity markers: time-varying short- and long-term memory, multiple regime shifts and sensitive dependence on initial conditions. Unexpectedly, self-ratings concerning physical sensations (e.g., the item `I am hungry') exhibited less complex dynamics and their behaviour was more similar to random variables. Conclusions: Psychological self-ratings display complex dynamics. The presence of complexity in repeated self-ratings means that we have to acknowledge that (1) repeated selfratings yield a complex pattern of data and not a set of (nearly) independent data points, (2)},
  file = {/home/aleksandar/Zotero/storage/VP4LUC2J/Olthof et al. - Complexity in Psychological Self-Ratings Implicat.pdf},
  language = {en}
}

@article{olthofCriticalFluctuationsEarlyWarning2020,
  title = {Critical {{Fluctuations}} as an {{Early}}-{{Warning Signal}} for {{Sudden Gains}} and {{Losses}} in {{Patients Receiving Psychotherapy}} for {{Mood Disorders}}},
  author = {Olthof, Merlijn and Hasselman, Fred and Strunk, Guido and {van Rooij}, Marieke and Aas, Benjamin and Helmich, Marieke A. and Schiepek, G{\"u}nter and {Lichtwarck-Aschoff}, Anna},
  year = {2020},
  month = jan,
  volume = {8},
  pages = {25--35},
  publisher = {{SAGE Publications Inc}},
  issn = {2167-7026},
  doi = {10.1177/2167702619865969},
  abstract = {Whereas sudden gains and losses (large shifts in symptom severity) in patients receiving psychotherapy appear abrupt and hence may seem unexpected, hypotheses from complex-systems theory suggest that sudden gains and losses are actually preceded by certain early-warning signals (EWSs). We tested whether EWSs in patients' daily self-ratings of the psychotherapeutic process predicted future sudden gains and losses. Data were collected from 328 patients receiving psychotherapy for mood disorders who completed daily self-ratings about their therapeutic process using the Therapy Process Questionnaire (TPQ). Sudden gains and losses were classified from the Problem Intensity scale of the TPQ. The other items of the TPQ were used to compute the EWSs. EWSs predicted an increased probability for sudden gains and losses in a 4-day predictive window. These results show that EWSs can be used for real-time prediction of sudden gains and losses in clinical practice.},
  file = {/home/aleksandar/Dropbox/Zotero/Olthof et al/Olthof et al_2020_Critical Fluctuations as an Early-Warning Signal for Sudden Gains and Losses in.pdf},
  journal = {Clinical Psychological Science},
  keywords = {complex systems,early-warning signals,mood disorders,open materials,preregistered,psychotherapy,sudden gains},
  language = {en},
  number = {1}
}

@article{olthofDestabilizationSelfratingsPsychotherapeutic2020,
  title = {Destabilization in Self-Ratings of the Psychotherapeutic Process Is Associated with Better Treatment Outcome in Patients with Mood Disorders},
  author = {Olthof, Merlijn and Hasselman, Fred and Strunk, Guido and Aas, Benjamin and Schiepek, G{\"u}nter and {Lichtwarck-Aschoff}, Anna},
  year = {2020},
  month = may,
  volume = {30},
  pages = {520--531},
  publisher = {{Routledge}},
  issn = {1050-3307},
  doi = {10.1080/10503307.2019.1633484},
  abstract = {Objective: While destabilization periods characterized by high variability and turbulence in a patient's psychological state might seem obstructive for psychotherapy, a complex systems approach to psychopathology predicts that these periods are actually beneficial as they indicate possibilities for reorganization within the patient. The present study tested the hypothesis that destabilization is related to better treatment outcome. Method: 328 patients who received psychotherapy for mood disorders completed daily self-ratings about their psychotherapeutic process. A continuous measure of destabilization was defined as the relative strength of the highest peak in dynamic complexity, a measure for variability and turbulence, in the self-ratings of individual patients. Results: Destabilization was found to be related to better treatment outcome. When improvers and non-improvers were analyzed separately, destabilization was found to be related to better treatment outcome in improvers but not in non-improvers. Conclusions: Destabilization in daily self-ratings of the psychotherapeutic process is associated with better treatment outcome. The identification of destabilization periods in process-monitoring data is clinically relevant. During destabilization, patients are believed to be increasingly sensitive to the effects of therapy. Clinicians could tailor their interventions to these sensitive periods.},
  annotation = {\_eprint: https://doi.org/10.1080/10503307.2019.1633484},
  file = {/home/aleksandar/Dropbox/Zotero/Olthof et al/Olthof et al_2020_Destabilization in self-ratings of the psychotherapeutic process is associated.pdf;/home/aleksandar/Zotero/storage/LYUQKAWL/10503307.2019.html},
  journal = {Psychotherapy Research},
  keywords = {change processes,complex systems,desestabilização,destabilization,mood disorders,processos de mudança,psicoterapia,psychotherapy,sistemas complexos,transtornos de humor,不穩定性,心理治療,情感性疾患,改變歷程,複雜系統},
  number = {4},
  pmid = {31256713}
}

@article{orlovicInfluenceElectoralSystem2015,
  title = {The Influence of Electoral System on Party Fragmentation in {{Serbian Parliament}}},
  author = {Orlovi{\'c}, Slavi{\v s}a},
  year = {2015},
  volume = {11},
  pages = {91--106},
  abstract = {The subject of this paper is the impact of electoral system and other factors on high fragmentation of the Parliament in Serbia. Party system in Serbia is still not institutionalized, even after 25 years of the introduction of the multiparty system. Two-round majority system was applied in the first multiparty elec-tions, and since 1992 the proportional system with the threshold of 5\% and D'Hondt formula has been in force. Since 2011 Serbia has closed electoral lists and mandates are allocated by the predetermined order. However, after the last elections in 2014 the Parliament in Serbia will have around 20 political parties, unions and other organizations. These stakeholders appear on the electoral lists of the major political parties or in pre-electoral coalitions without graded elec-toral threshold and after entering the parliament form a separate parliamentary group, or distinguish themselves with their own identity, which leads to indirect parliamentarization and fragmentation of the parliament. This reflects on the complexity of the process of (coalition) government formation, but also on the functioning of the parliament. Frequent blackmails from the smaller political parties or changes in the behavior of actors reduce the predictability of actors' actions and slow down the consolidation of democracy in Serbia.},
  journal = {Serbian Political Thought},
  number = {1/2015}
}

@article{orlovicInfluenceElectoralSystem2015a,
  title = {The Influence of Electoral System on Party Fragmentation in {{Serbian Parliarment}}},
  author = {Orlovi{\'c}, Slavi{\v s}a},
  year = {2015},
  volume = {11},
  pages = {91--106},
  journal = {Serbian Political Thought},
  number = {1}
}

@article{orlovicPartiesPartySystem2008,
  title = {Parties and the Party System of {{Serbia}} and {{European}} Integrations},
  author = {Orlovi{\'C}, Slavi{\v S}a},
  year = {2008},
  month = aug,
  volume = {10},
  pages = {205--222},
  issn = {1461-3190, 1469-963X},
  doi = {10.1080/14613190802146356},
  journal = {Journal of Southern Europe and the Balkans},
  language = {en},
  number = {2}
}

@incollection{orlovicPartijskiSistemSrbije2011,
  title = {Partijski Sistem {{Srbije}}},
  booktitle = {Partije i Izbori u {{Srbiji}} - 20 Godina},
  author = {Orlovi{\'c}, Slavi{\v s}a},
  editor = {Orlovi{\'c}, Slavi{\v s}a},
  year = {2011},
  pages = {7--11},
  publisher = {{\v{C}igoja \v{s}tampa}},
  address = {{Beograd}}
}

@incollection{ormanEmpiricalStudyRelation2013,
  title = {An {{Empirical Study}} of the {{Relation}} between {{Community Structure}} and {{Transitivity}}},
  booktitle = {Complex {{Networks}}},
  author = {Orman, Keziban and Labatut, Vincent and Cherifi, Hocine},
  editor = {Menezes, Ronaldo and Evsukoff, Alexandre and Gonz{\'a}lez, Marta C.},
  year = {2013},
  volume = {424},
  pages = {99--110},
  publisher = {{Springer Berlin Heidelberg}},
  address = {{Berlin, Heidelberg}},
  doi = {10.1007/978-3-642-30287-9_11},
  file = {/home/aleksandar/Documents/Zotero/Orman et al/Orman et al_2013_An Empirical Study of the Relation between Community Structure and Transitivity.pdf},
  isbn = {978-3-642-30286-2 978-3-642-30287-9}
}

@article{ornsteinStackedRegressionPoststratification,
  title = {Stacked {{Regression}} and {{Poststratification}}},
  author = {Ornstein, Joseph T.},
  doi = {10.1017/pan.2019.43},
  abstract = {I develop a procedure for estimating local-area public opinion called stacked regression and poststratification (SRP), a generalization of classical multilevel regression and poststratification (MRP). This procedure employs a diverse ensemble of predictive models\textemdash including multilevel regression, LASSO, k-nearest neighbors, random forest, and gradient boosting\textemdash to improve the cross-validated fit of the first-stage predictions. In a Monte Carlo simulation, SRP significantly outperforms MRP when there are deep interactions in the data generating process, without requiring the researcher to specify a complex parametric model in advance. In an empirical application, I show that SRP produces superior local public opinion estimates on a broad range of issue areas, particularly when trained on large datasets.},
  journal = {Political Analysis}
}

@article{orouskhaniMultiobjectiveEvolutionaryClustering2021,
  title = {Multi-Objective Evolutionary Clustering with Complex Networks},
  author = {Orouskhani, Maysam and Shi, Daming and Orouskhani, Yasin},
  year = {2021},
  month = mar,
  volume = {165},
  pages = {113916},
  issn = {0957-4174},
  doi = {10.1016/j.eswa.2020.113916},
  abstract = {Evolutionary clustering (EC) refers to the applications of evolutionary optimization algorithms such as genetic algorithm to data clustering. Although multi-objective evolutionary clustering algorithms were proposed to simultaneously consider different cluster properties such as compactness and separation, these techniques usually suffer from a reasonable initial population and a pre-defined number of clusters. Besides, the effectiveness of evolutionary operators is decreased in dealing with the clustering problem. On the other side, complex networks play an essential role in different fields of machine learning. In a complex network, points are considered as nodes, and the dataset is shown as a connected weighted graph. Also, complex networks tend to present a modular structure. This paper applies two concepts of complex networks including node centrality and community modularity to introduce a novel multi-objective evolutionary clustering. The proposed centrality modularity-based multi-objective evolutionary clustering (CMMOEC) takes the advantage of nodes similarity to find the best initial population of clustering solutions and provide new structural-based modularity to determine the optimal number of clusters automatically. Moreover, the proposed modularity is used to design a new recombination and mutation operator so that it generates offspring solutions that satisfy more diversity. Experiments carried out on several artificial and real-world datasets with different structures. The performance of the proposed algorithm is evaluated by the Adjusted Rand Index (ARI). Simulation results indicate that the proposed algorithm satisfies better performance in comparison to traditional methods.},
  file = {/home/aleksandar/Zotero/storage/2USXXLHP/S0957417420307090.html},
  journal = {Expert Systems with Applications},
  language = {en}
}

@techreport{osmundsenPsychophysiologyPoliticalIdeology2019,
  title = {The {{Psychophysiology}} of {{Political Ideology}}: {{Replications}}, {{Reanalysis}} and {{Recommendations}}},
  shorttitle = {The {{Psychophysiology}} of {{Political Ideology}}},
  author = {Osmundsen, Mathias and Hendry, David and Laustsen, Lasse and Smith, Kevin and Petersen, Michael Bang},
  year = {2019},
  month = jun,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/49hfg},
  abstract = {This manuscript presents a large-scale, empirical evaluation of the psychophysiological correlates of political ideology and, in particular, the claim that conservatives react with higher levels of electrodermal activity to threatening stimuli than liberals. We (1) conduct two large replications of this claim, using locally representative samples of Danes and Americans; (2) re-analyze all published studies and evaluate their reliability and validity; and (3) test several features to enhance the validity of psychophysiological measures and offer a number of recommendations. Overall, we find little empirical support for the claim. This is caused by significant reliability and validity problems related to measuring threat-sensitivity using electrodermal activity. When assesed reliably, electrodermal activity in the replications and published studies captures individual differences in the physiological changes associated with attention shifts, which are unrelated to ideology. In contrast to psychophysiological reactions, self-reported emotional reactions to threatening stimuli are reliably associated with ideology.},
  language = {en},
  type = {Preprint}
}

@article{overgoorChoosingGrowGraph,
  title = {Choosing to Grow a Graph: {{Modeling}} Network Formation as Discrete Choice.},
  author = {Overgoor, Jan and Benson, Austin R. and Ugander, Johan},
  doi = {arXiv:1811.05008v1},
  abstract = {{$<$}p{$>$}We provide a framework for modeling social network formation through conditional multinomial logit models from discrete choice and random utility theory, in which each new edge is viewed as a "choice" made by a node to connect to another node, based on (generic) features of the other nodes available to make a connection. This perspective on network formation unifies existing models such as preferential attachment, triadic closure, and node fitness, which are all special cases, and thereby provides a flexible means for conceptualizing, estimating, and comparing models. The lens of discrete choice theory also provides several new tools for analyzing social network formation; for example, mixtures of existing models can be estimated by adapting known expectation-maximization algorithms, and the significance of node features can be evaluated in a statistically rigorous manner. We demonstrate the flexibility of our framework through examples that analyze a number of synthetic and real-world datasets. For example, we provide rigorous methods for estimating preferential attachment models and show how to separate the effects of preferential attachment and triadic closure. Non-parametric estimates of the importance of degree show a highly linear trend, and we expose the importance of looking carefully at nodes with degree zero. Examining the formation of a large citation graph, we find evidence for an increased role of degree when accounting for age. {$<$}/p{$>$}},
  journal = {arXiv Physics and Society}
}

@article{overgoorChoosingGrowGrapha,
  title = {Choosing to Grow a Graph: {{Modeling}} Network Formation as Discrete Choice.},
  author = {Overgoor, Jan and Benson, Austin R. and Ugander, Johan},
  doi = {arXiv:1811.05008v1},
  abstract = {{$<$}p{$>$}We provide a framework for modeling social network formation through conditional multinomial logit models from discrete choice and random utility theory, in which each new edge is viewed as a "choice" made by a node to connect to another node, based on (generic) features of the other nodes available to make a connection. This perspective on network formation unifies existing models such as preferential attachment, triadic closure, and node fitness, which are all special cases, and thereby provides a flexible means for conceptualizing, estimating, and comparing models. The lens of discrete choice theory also provides several new tools for analyzing social network formation; for example, mixtures of existing models can be estimated by adapting known expectation-maximization algorithms, and the significance of node features can be evaluated in a statistically rigorous manner. We demonstrate the flexibility of our framework through examples that analyze a number of synthetic and real-world datasets. For example, we provide rigorous methods for estimating preferential attachment models and show how to separate the effects of preferential attachment and triadic closure. Non-parametric estimates of the importance of degree show a highly linear trend, and we expose the importance of looking carefully at nodes with degree zero. Examining the formation of a large citation graph, we find evidence for an increased role of degree when accounting for age. {$<$}/p{$>$}},
  journal = {arXiv Physics and Society}
}

@article{overgoorScalingChoiceModels2020,
  title = {Scaling {{Choice Models}} of {{Relational Social Data}}},
  author = {Overgoor, Jan and Supaniratisai, George Pakapol and Ugander, Johan},
  year = {2020},
  month = jun,
  abstract = {Many prediction problems on social networks, from recommendations to anomaly detection, can be approached by modeling network data as a sequence of relational events and then leveraging the resulting model for prediction. Conditional logit models of discrete choice are a natural approach to modeling relational events as "choices" in a framework that envelops and extends many long-studied models of network formation. The conditional logit model is simplistic, but it is particularly attractive because it allows for efficient consistent likelihood maximization via negative sampling, something that isn't true for mixed logit and many other richer models. The value of negative sampling is particularly pronounced because choice sets in relational data are often enormous. Given the importance of negative sampling, in this work we introduce a model simplification technique for mixed logit models that we call "de-mixing", whereby standard mixture models of network formation---particularly models that mix local and global link formation---are reformulated to operate their modes over disjoint choice sets. This reformulation reduces mixed logit models to conditional logit models, opening the door to negative sampling while also circumventing other standard challenges with maximizing mixture model likelihoods. To further improve scalability, we also study importance sampling for more efficiently selecting negative samples, finding that it can greatly speed up inference in both standard and de-mixed models. Together, these steps make it possible to much more realistically model network formation in very large graphs. We illustrate the relative gains of our improvements on synthetic datasets with known ground truth as well as a large-scale dataset of public transactions on the Venmo platform.},
  archivePrefix = {arXiv},
  eprint = {2006.10003},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Overgoor et al/Overgoor et al_2020_Scaling Choice Models of Relational Social Data.pdf;/home/aleksandar/Zotero/storage/JVMFEH98/2006.html},
  journal = {arXiv:2006.10003 [cs]},
  keywords = {_tablet},
  primaryClass = {cs}
}

@article{palacio-ninoUseLocalStructural2020,
  title = {On the Use of Local Structural Properties for Improving the Efficiency of Hierarchical Community Detection Methods},
  author = {{Palacio-Ni{\~n}o}, Julio-Omar and Berzal, Fernando},
  year = {2020},
  month = sep,
  abstract = {Community detection is a fundamental problem in the analysis of complex networks. It is the analogue of clustering in network data mining. Within community detection methods, hierarchical algorithms are popular. However, their iterative nature and the need to recompute the structural properties used to split the network (i.e. edge betweenness in Girvan and Newman's algorithm), make them unsuitable for large network data sets. In this paper, we study how local structural network properties can be used as proxies to improve the efficiency of hierarchical community detection while, at the same time, achieving competitive results in terms of modularity. In particular, we study the potential use of the structural properties commonly used to perform local link prediction, a supervised learning problem where community structure is relevant, as nodes are prone to establish new links with other nodes within their communities. In addition, we check the performance impact of network pruning heuristics as an ancillary tactic to make hierarchical community detection more efficient},
  archivePrefix = {arXiv},
  eprint = {2009.06798},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/X7BW4594/Palacio-Niño_Berzal_2020_On the use of local structural properties for improving the efficiency of.pdf;/home/aleksandar/Zotero/storage/4ZRT5II5/2009.html},
  journal = {arXiv:2009.06798 [cs, stat]},
  primaryClass = {cs, stat}
}

@article{palAsymptoticDegreeDistributions,
  title = {Asymptotic Degree Distributions in Large (Homogeneous) Random Networks: {{A}} Little Theory and a Counterexample.},
  author = {Pal, Siddharth and Makowski, Armand M.},
  doi = {arXiv:1710.11064v3},
  abstract = {{$<$}p{$>$}In random graph models, the degree distribution of an individual node should be distinguished from the (empirical) degree distribution of the graph that records the fractions of nodes with given degree. We introduce a general framework to explore when these two degree distributions coincide asymptotically in large homogeneous random networks. The discussion is carried under three basic statistical assumptions on the degree sequences: (i) a weak form of distributional homogeneity; (ii) the existence of an asymptotic (nodal) degree distribution; and (iii) a weak form of asymptotic uncorrelatedness. We show that this asymptotic equality may fail in homogeneous random networks for which (i) and (ii) hold but (iii) does not. The counterexample is found in the class of random threshold graphs. An implication of this finding is that random threshold graphs cannot be used as a substitute to the Barab\textbackslash 'asi-Albert model for scale-free network modeling, as has been proposed by some authors. The results can also be formulated for non-homogeneous models by making use of a random sampling procedure over the nodes. {$<$}/p{$>$}},
  journal = {arXiv Physics and Society}
}

@article{palAsymptoticDegreeDistributionsa,
  title = {Asymptotic Degree Distributions in Large (Homogeneous) Random Networks: {{A}} Little Theory and a Counterexample.},
  author = {Pal, Siddharth and Makowski, Armand M.},
  doi = {arXiv:1710.11064v3},
  abstract = {{$<$}p{$>$}In random graph models, the degree distribution of an individual node should be distinguished from the (empirical) degree distribution of the graph that records the fractions of nodes with given degree. We introduce a general framework to explore when these two degree distributions coincide asymptotically in large homogeneous random networks. The discussion is carried under three basic statistical assumptions on the degree sequences: (i) a weak form of distributional homogeneity; (ii) the existence of an asymptotic (nodal) degree distribution; and (iii) a weak form of asymptotic uncorrelatedness. We show that this asymptotic equality may fail in homogeneous random networks for which (i) and (ii) hold but (iii) does not. The counterexample is found in the class of random threshold graphs. An implication of this finding is that random threshold graphs cannot be used as a substitute to the Barab\textbackslash 'asi-Albert model for scale-free network modeling, as has been proposed by some authors. The results can also be formulated for non-homogeneous models by making use of a random sampling procedure over the nodes. {$<$}/p{$>$}},
  journal = {arXiv Physics and Society}
}

@book{PalgraveHandbookSurvey2017,
  title = {The {{Palgrave}} Handbook of Survey Research},
  year = {2017},
  publisher = {{Springer Berlin Heidelberg}},
  address = {{New York, NY}},
  isbn = {978-3-319-54394-9}
}

@article{panayiotouExploringDimensionalitySocial2020,
  title = {Exploring the {{Dimensionality}} of the {{Social Skills Improvement System Using Exploratory Graph Analysis}} and {{Bifactor}}-( {{{\emph{S}}}} - 1) {{Modeling}}},
  author = {Panayiotou, Margarita and Santos, Jo{\~a}{$o$} and Black, Louise and Humphrey, Neil},
  year = {2020},
  month = nov,
  pages = {107319112097135},
  issn = {1073-1911, 1552-3489},
  doi = {10.1177/1073191120971351},
  abstract = {Since its development over a decade ago, the Social Skills Improvement System (SSIS) has been one of the most widely used measures of social skills in children. However, evidence of its structural validity has been scant. The current study examined the original seven-factor and more recent five-factor structure (SSIS-SEL) of the self-report SSIS in a sample of English elementary school students (N = 3,331) aged 8 to 10 years (M = 8.66, SD = 0.59). A problematic fit was found for both structures with poor discriminant validity. Using exploratory graph analysis and bifactor-(S - 1) modeling, we found support for a four-factor structure, the variation of which was captured by a general factor defined by ``empathy and prosocial skills.'' Future researchers, particularly those interested in using specific domains of the SSIS, are urged to assess its structure in their studies, if their findings are to be theoretically meaningful.},
  file = {/home/aleksandar/Zotero/storage/FH8EYEGK/Panayiotou et al. - 2020 - Exploring the Dimensionality of the Social Skills .pdf},
  journal = {Assessment},
  language = {en}
}

@article{pankowskaHowLinkageError,
  title = {How {{Linkage Error Affects Hidden Markov Model Estimates}}: {{A Sensitivity Analysis}}},
  shorttitle = {How {{Linkage Error Affects Hidden Markov Model Estimates}}},
  author = {Pankowska, Paulina and Bakker, Bart F. M. and Oberski, Daniel L. and Pavlopoulos, Dimitris},
  doi = {10.1093/jssam/smz011},
  abstract = {Abstract.  Hidden Markov models (HMMs) are increasingly used to estimate and correct for classification error in categorical, longitudinal data, without the nee},
  file = {/home/aleksandar/Zotero/storage/ZMU76R5R/5506582.html},
  journal = {Journal of Survey Statistics and Methodology},
  language = {en}
}

@article{panovVolatilityElectoralSupport2019,
  title = {Volatility in {{Electoral Support}} for {{United Russia}}: {{Cross}}-{{Regional Variations}} in {{Putin}}'s {{Electoral Authoritarian Regime}}},
  shorttitle = {Volatility in {{Electoral Support}} for {{United Russia}}},
  author = {Panov, Petr and Ross, Cameron},
  year = {2019},
  month = feb,
  volume = {71},
  pages = {268--289},
  issn = {0966-8136, 1465-3427},
  doi = {10.1080/09668136.2018.1563050},
  journal = {Europe-Asia Studies},
  language = {en},
  number = {2}
}

@article{panUsingDiscontinuationRule2019,
  title = {Using the Discontinuation Rule to Reduce the Effect of Random Guessing on Parameter Estimation in the Item Response Theory},
  author = {Pan, Tianshu and Cho, Youngmi},
  year = {2019},
  month = nov,
  issn = {1349-6964},
  doi = {10.1007/s41237-019-00101-8},
  abstract = {The discontinuation rule is often used to reduce the effect of random guessing in psychological tests. It may also play the similar role in the item response theory. In this article, a Monte Carlo study was implemented to explore the feasibility of the four- and six-consecutive-zero discontinuation rules to reduce the effect of random guessing on parameter estimation in the Rasch model. The results showed that random guessing inflated estimation errors, and these discontinuation rules can reduce this effect on item-parameter estimation under the joint and marginal maximum likelihood, but can do so only for person-parameter estimation under the marginal maximum likelihood and expected a posteriori methods.},
  journal = {Behaviormetrika},
  language = {en}
}

@article{paolilloSimulatingAcculturationDynamics,
  ids = {paolilloSimulatingAcculturationDynamic,paolilloSimulatingAcculturationDynamicsa,paolilloSimulatingAcculturationDynamicsb},
  title = {Simulating Acculturation Dynamics between Migrants and Locals in Relation to Network Formation.},
  author = {Paolillo, Rocco and Jager, Wander},
  doi = {arXiv:1810.02650v2},
  abstract = {{$<$}p{$>$}International migration implies the coexistence of different ethnic and cultural groups in the receiving country. The refugee crisis of 2015 has resulted in critical levels of opinion polarization on the question of whether to welcome migrants, causing clashes in receiving countries. This scenario emphasizes the need to better understand the dynamics of mutual adaptation between locals and migrants, and the conditions that favor successful integration. Agent-based simulations can help achieve this goal. In this work, we introduce our model MigrAgent and our preliminary results. The model synthesizes the dynamics of migration intake and post-migration adaptation. It explores the different acculturation outcomes that can emerge from the mutual adaptation of a migrant population and a local population depending on their degree of tolerance. With parameter sweeping, we detect how different acculturation strategies can coexist in a society and in different degrees among various subgroups. The results show higher polarization effects between a local population and a migrant population for fast intake conditions. When migrant intake is slow, transitory conditions between acculturation outcomes emerge for subgroups, e.g., from assimilation to integration for liberal migrants and from marginalization to separation for conservative migrants. Relative group sizes due to speed of intake cause counterintuitive scenarios, such as the separation of liberal locals. We qualitatively compare the processes of our model with the German portion sample of the survey Causes and Consequences of Socio-Cultural Integration Processes among New Immigrants in Europe (SCIP), finding preliminary confirmation of our assumptions and results. {$<$}/p{$>$}},
  journal = {arXiv Computer Science}
}

@article{papakyriakopoulosPoliticalMachinesMachine,
  title = {Political Machines: Machine Learning for Understanding the Politics of Social Machines},
  author = {Papakyriakopoulos, Orestis},
  pages = {158},
  file = {/home/aleksandar/Zotero/storage/6WVYRNW9/Papakyriakopoulos - Political machines machine learning for understan.pdf},
  language = {en}
}

@article{pareschiHydrodynamicModelsPreference,
  title = {Hydrodynamic Models of Preference Formation in Multi-Agent Societies.},
  author = {Pareschi, Lorenzo and Toscani, Giuseppe and Tosin, Andrea and Zanella, Mattia},
  doi = {arXiv:1901.00486v1},
  abstract = {{$<$}p{$>$}In this paper, we discuss the passage to hydrodynamic equations for kinetic models of opinion formation. The considered kinetic models feature an opinion density depending on an additional microscopic variable, identified with the personal preference. This variable describes an opinion-driven polarisation process, leading finally to a choice among some possible options, as it happens e.g. in referendums or elections. Like in the kinetic theory of rarefied gases, the derivation of hydrodynamic equations is essentially based on the computation of the local equilibrium distribution of the opinions from the underlying kinetic model. Several numerical examples validate the resulting model, shedding light on the crucial role played by the distinction between opinion and preference formation on the choice processes in multi-agent societies. {$<$}/p{$>$}},
  journal = {arXiv Physics and Society}
}

@article{parkReviewAdvancesLatent2019,
  title = {Review of {{Advances}} in {{Latent Class Analysis}}},
  author = {Park, Yoon Soo and Lin, Qiao},
  year = {2019},
  month = nov,
  issn = {1860-0980},
  doi = {10.1007/s11336-019-09690-5},
  journal = {Psychometrika},
  language = {en}
}

@book{parsonsGeneralTheoryAction1992,
  ids = {parsonsGeneralTheoryAction1962},
  title = {Toward a General Theory of Action},
  editor = {Parsons, Talcott},
  year = {1992},
  publisher = {{UMI}},
  address = {{Ann Arbor, Mich}},
  annotation = {OCLC: 258633632},
  isbn = {978-0-674-89655-0},
  language = {eng}
}

@book{parsonsSocialStructurePersonality1970,
  title = {Social Structure and Personality},
  author = {Parsons, Talcott},
  year = {1970},
  annotation = {OCLC: 960947292},
  isbn = {978-1-4391-3830-4},
  language = {English}
}

@article{passosExtremaAnalysisNode2020,
  title = {Extrema {{Analysis}} of {{Node Centrality}} in {{Weighted Networks}}},
  author = {Passos, Roger S. and Cardoso, Douglas O.},
  year = {2020},
  month = nov,
  abstract = {A very interesting matter of Network Science is assessing how complex a given network is. In other words, by how much does such a network departs from any general patterns which could be evoked for its description. Among other choices, these patterns can be defined in terms of node or edge properties, as one of the various modes of centrality. Although there are centrality indexes defined for weighted graphs, the discussions on this subject are far from over, especially because the influence of edge weights in this regard can vary not only in form but also in intensity, a still incipient approach so far. For the aforementioned complexity evaluation, the situation is even more acute: to the best of our knowledge, this was never addressed in the literature, from the standpoint of centrality in weighted graphs. This paper details in a colorful fashion a sound methodology covering both topics, as well as experiments confirming its practical applicability and future trends in this context.},
  archivePrefix = {arXiv},
  eprint = {2011.00429},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Passos_Cardoso/Passos_Cardoso_2020_Extrema Analysis of Node Centrality in Weighted Networks.pdf;/home/aleksandar/Zotero/storage/AU649BGL/2011.html},
  journal = {arXiv:2011.00429 [cs]},
  keywords = {Computer Science - Social and Information Networks},
  primaryClass = {cs}
}

@inproceedings{pattanayakRelationshipCommunityStructure2021,
  title = {Relationship {{Between Community Structure}} and {{Clustering Coefficient}}},
  booktitle = {Intelligent {{Computing}} and {{Applications}}},
  author = {Pattanayak, Himansu Sekhar and Verma, Harsh K. and Sangal, A. L.},
  editor = {Dash, Subhransu Sekhar and Das, Swagatam and Panigrahi, Bijaya Ketan},
  year = {2021},
  pages = {203--220},
  publisher = {{Springer}},
  address = {{Singapore}},
  doi = {10.1007/978-981-15-5566-4_18},
  abstract = {Overlapping community is a phenomenon often observed in numerous real-world networks. Fire-spread (Pattanayak et al. in Swarm Evol Comput. 44: 1\textendash 48 (2019) [11]) community detection algorithm is an efficient algorithm to detect overlapping community structures. In this work, the Fire-spread algorithm is modified to establish a relationship between community structure and clustering coefficient. By using different networks and executing the modified Fire-spread algorithm, it is found that the clustering coefficient is highly correlated with community structure. Finally, a simpler community detection algorithm, derived from the fire-spread algorithm, is proposed, where the clustering coefficient is used as a threshold value. To validate the proposed algorithm, it is compared with some state of art community detection algorithms based on the NMI score.},
  isbn = {9789811555664},
  language = {en},
  series = {Advances in {{Intelligent Systems}} and {{Computing}}}
}

@incollection{pavasovictrostReligionHomosexualityNationalism2015,
  title = {Religion, {{Homosexuality}} and {{Nationalism}} in the {{Western Balkans}}: {{The Role}} of {{Religious Institutions}} in {{Defining}} the {{Nation}}},
  shorttitle = {Religion, {{Homosexuality}} and {{Nationalism}} in the {{Western Balkans}}},
  booktitle = {Religious and {{Sexual Nationalisms}} in {{Central}} and {{Eastern Europe}}},
  author = {Pavasovi{\'c} Tro{\v s}t, Tamara and Slootmaeckers, Koen},
  editor = {Sremac, Srdjan and Ganzevoort, R. Ruard},
  year = {2015},
  month = jan,
  publisher = {{BRILL}},
  doi = {10.1163/9789004297791_010},
  isbn = {978-90-04-29779-1 978-90-04-29747-0}
}

@article{pavlovicGlobalCulturalZones2019,
  title = {Global Cultural Zones the Empirical Way: Value Structure of Cultural Zones and Their Relationship with Democracy and the Communist Past},
  shorttitle = {Global Cultural Zones the Empirical Way},
  author = {Pavlovi{\'c}, Zoran and Todosijevi{\'c}, Bojan},
  year = {2019},
  month = mar,
  issn = {1573-7845},
  doi = {10.1007/s11135-019-00861-1},
  abstract

license: MIT

repository: atomashevic/website-at

license_type: permissive

repo_name: atomashevic/website-at

branch_name: refs/heads/master

extension: bib