text:
its Applications{$<$}/p{$><$}p{$>$}Author(s): Marcos E. Gaudiano, Jorge A. Revelli{$<$}/p{$><$}h5{$>$}Abstract{$<$}/h5{$><$}div{$><$}p{$>$}Opinion dynamics is one of the most studied problems in sociophysics. Many easy-to-analyze dynamical systems are modelled in a language of agent-based numerical procedures in order to provide new insights for understanding collective phenomena.{$<$}/p{$><$}p{$>$}The present work is devoted to analyze the effects of spatial heterogeneties in the initial topological map of agent ideas. In the spirit of the statistical physics of social impact, we study the consequences of running a Sznajd model into a structured opinion formation dynamics of a given social community. We carry out a spatio-temporal fractal analysis of the ideological configuration map, showing novel features belonging to different initial conditions. By performing numerical simulations, we mainly show how the evolution of ideas can lead to a spontaneous emergence of a third ideological position. This emergence is just characterized by few parameters: the dimensionality of the initial ideological structures and the interaction dynamics. No additional external constraints are assumed. Moreover, different emergent behaviors in the limit of high participation apathy are observed.{$<$}/p{$><$}/div{$>$}},
  journal = {Physica A: Statistical Mechanics and its Applications}
}

@article{gavriletsCollectiveActionEvolution,
  title = {Collective Action and the Evolution of Social Norm Internalization [{{Anthropology}}]},
  author = {Gavrilets, Sergey and Richerson, Peter J.},
  doi = {10.1073/pnas.1703857114},
  abstract = {{$<$}p id="p-6"{$>$}Human behavior is strongly affected by culturally transmitted norms and values. Certain norms are internalized (i.e., acting                               according to a norm becomes an end in itself rather than merely a tool in achieving certain goals or avoiding social sanctions).                               Humans' capacity to internalize norms likely evolved in our ancestors to simplify solving certain challenges\textemdash including social                               ones. Here we study theoretically the evolutionary origins of the capacity to internalize norms. In our models, individuals                               can choose to participate in collective actions as well as punish free riders. In making their decisions, individuals attempt                               to maximize a utility function in which normative values are initially irrelevant but play an increasingly important role                               if the ability to internalize norms emerges. Using agent-based simulations, we show that norm internalization evolves under                               a wide range of conditions so that cooperation becomes ``instinctive.'' Norm internalization evolves much more easily and has                               much larger effects on behavior if groups promote peer punishment of free riders. Promoting only participation in collective                               actions is not effective. Typically, intermediate levels of norm internalization are most frequent but there are also cases                               with relatively small frequencies of ``oversocialized'' individuals willing to make extreme sacrifices for their groups no matter                               material costs, as well as ``undersocialized'' individuals completely immune to social norms. Evolving the ability to internalize                               norms was likely a crucial step on the path to large-scale human cooperation.                            {$<$}/p{$>$}},
  journal = {Proceedings of the National Academy of Sciences of the United States of America}
}

@article{gawronskiBackFutureDissonance2012,
  title = {Back to the {{Future}} of {{Dissonance Theory}}: {{Cognitive Consistency}} as a {{Core Motive}}},
  shorttitle = {Back to the {{Future}} of {{Dissonance Theory}}},
  author = {Gawronski, Bertram},
  year = {2012},
  month = dec,
  volume = {30},
  pages = {652--668},
  issn = {0278-016X},
  doi = {10.1521/soco.2012.30.6.652},
  journal = {Social Cognition},
  language = {en},
  number = {6}
}

@article{gelmanHolesBayesianStatistics2020,
  title = {Holes in {{Bayesian Statistics}}},
  author = {Gelman, Andrew and Yao, Yuling},
  year = {2020},
  month = feb,
  abstract = {Every philosophy has holes, and it is the responsibility of proponents of a philosophy to point out these problems. Here are a few holes in Bayesian data analysis: (1) the usual rules of conditional probability fail in the quantum realm, (2) flat or weak priors lead to terrible inferences about things we care about, (3) subjective priors are incoherent, (4) Bayes factors fail in the presence of flat or weak priors, (5) for Cantorian reasons we need to check our models, but this destroys the coherence of Bayesian inference.},
  archivePrefix = {arXiv},
  eprint = {2002.06467},
  eprinttype = {arxiv},
  journal = {arXiv:2002.06467 [math, stat]},
  language = {en},
  primaryClass = {math, stat}
}

@article{geLPXOverlappingCommunity,
  title = {{{LPX}}: {{Overlapping}} Community Detection Based on {{X}}-Means and Label Propagation Algorithm in Attributed Networks},
  shorttitle = {{{LPX}}},
  author = {Ge, Jinhuan and Sun, Heli and Xue, Chenhao and He, Liang and Jia, Xiaolin and He, Hui and Chen, Jiyin},
  volume = {n/a},
  issn = {1467-8640},
  doi = {10.1111/coin.12420},
  abstract = {Traditional community detection methods in attributed networks (eg, social network) usually disregard abundant node attribute information and only focus on structural information of a graph. Existing community detection methods in attributed networks are mostly applied in the detection of nonoverlapping communities and cannot be directly used to detect the overlapping structures. This article proposes an overlapping community detection algorithm in attributed networks. First, we employ the modified X-means algorithm to cluster attributes to form different themes. Second, we employ the label propagation algorithm (LPA), which is based on neighborhood network conductance for priority and the rule of theme weight, to detect communities in each theme. Finally, we perform redundant processing to form the final community division. The proposed algorithm improves the X-means algorithm to avoid the effects of outliers. Problems of LPA such as instability of division and adjacent communities being easily merged can be corrected by prioritizing the node neighborhood network conductance. As the community is detected in the attribute subspace, the algorithm can find overlapping communities. Experimental results on real-attributed and synthetic-attributed networks show that the performance of the proposed algorithm is excellent with multiple evaluation metrics.},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/coin.12420},
  copyright = {\textcopyright{} 2020 Wiley Periodicals LLC.},
  journal = {Computational Intelligence},
  keywords = {attributed network,community detection,overlapping community},
  language = {en},
  number = {n/a}
}

@misc{GeneralizedNetworkPsychometrics,
  title = {Generalized {{Network Psychometrics}}: {{Combining Network}} and {{Latent Variable Models}} | {{SpringerLink}}},
  howpublished = {https://link.springer.com/article/10.1007/s11336-017-9557-x}
}

@misc{GeneralizedNetworkPsychometricsa,
  title = {Generalized {{Network Psychometrics}}: {{Combining Network}} and {{Latent Variable Models}} | {{SpringerLink}}},
  howpublished = {https://link.springer.com/article/10.1007/s11336-017-9557-x}
}

@article{gengeAreAttitudesImmigration,
  title = {Are Attitudes towards Immigration Changing in {{Europe}}? {{An}} Analysis Based on Bidimensional Latent Class {{IRT}} Models},
  author = {Genge, Ewa},
  pages = {27},
  abstract = {We analyse the changing attitudes towards immigration in EU host countries in the last few years (2010-2016) on the basis of the European Social Survey data. These data are collected by the administration of a questionnaire made of items concerning different aspects related to the immigration phenomenon. For this analysis we rely on a class of item response theory models that allow for: (i) multidimensionality; (ii) discreteness of the latent trait distribution; (iii) time-constant and time-varying covariates; and (iv) sample weights. Through these models we find latent classes of Europeans with similar levels of immigration acceptance, we study the effect of different socio-economic covariates on the probability of belonging to these classes, and we assess the item characteristics. In this way we show which countries tend to be more or less positive towards immigration and the temporal dynamics of the phenomenon under study.},
  language = {en}
}

@article{gerringElectoralContestationNew,
  title = {Electoral {{Contestation}}:1 {{A New Measure}} and an {{Empirical Test}}},
  author = {Gerring, John and Hicken, Allen and Weitzel, Daniel},
  pages = {41},
  abstract = {The study of electoral competition generally focuses on districts or regions (rather than polities) or a narrow slice of democratic polities. We present a new national-level dataset that registers the performance of the top three parties in elections held in sovereign and semi-sovereign polities throughout the world from 1789 to the present. With this data, we present a new approach to aggregation that incorporates three components of contestation: the existence of elections, the closeness of the vote (competitiveness), and changes in performance of the top parties (turnover). To illustrate the utility of this new index we explore its possible impact on government consumption. We find that contestation has a curvilinear \textendash{} inverted U \textendash{} relationship to this outcome, a relationship not revealed with indices focused more narrowly on competitiveness.},
  file = {/home/aleksandar/Dropbox/Zotero/Gerring et al/Gerring et al_Electoral Contestation.pdf},
  language = {en}
}

@article{gerringOrdinalConceptdrivenApproach2018,
  title = {An {{Ordinal}}, {{Concept}}-Driven {{Approach}} to {{Measurement}}: {{The Lexical Scale}}},
  shorttitle = {An {{Ordinal}}, {{Concept}}-Driven {{Approach}} to {{Measurement}}},
  author = {Gerring, John and Pemstein, Daniel and Skaaning, Svend-Erik},
  year = {2018},
  month = jul,
  pages = {0049124118782531},
  issn = {0049-1241},
  doi = {10.1177/0049124118782531},
  abstract = {A key obstacle to measurement is the aggregation problem. Where indicators tap into common latent traits in theoretically meaningful ways, the problem may be solved by applying a data-informed (``inductive'') measurement model, for example, factor analysis, structural equation models, or item response theory. Where they do not, researchers solve the aggregation problem by appeal to concept-driven (``deductive'') criteria, that is, aggregation schemes that do not presume patterns of covariance across observable indicators. This article introduces a novel approach to scale construction that builds on the properties of concepts to solve the aggregation problem. This is accomplished by regarding conceptual attributes as necessary-and-sufficient conditions arrayed in an ordinal scale. While different sorts of scales are useful for different purposes, we argue that ``lexical'' scales are in many cases superior for research questions where it is relevant to combine the differentiation of an ordinal scale with the distinct, meaningful categories of a typology.},
  journal = {Sociological Methods \& Research},
  language = {en}
}

@article{gersbachCostsChangePolitical2019,
  title = {Costs of Change and Political Polarization},
  author = {Gersbach, Hans and Muller, Philippe and Tejada, Oriol},
  year = {2019},
  month = jul,
  pages = {S0176268018303331},
  issn = {01762680},
  doi = {10.1016/j.ejpoleco.2019.06.002},
  journal = {European Journal of Political Economy},
  language = {en}
}

@article{ghaffarStructuralHoleCentrality2020,
  title = {Structural Hole Centrality: Evaluating Social Capital through Strategic Network Formation},
  shorttitle = {Structural Hole Centrality},
  author = {Ghaffar, Faisal and Hurley, Neil},
  year = {2020},
  month = sep,
  volume = {7},
  pages = {5},
  issn = {2197-4314},
  doi = {10.1186/s40649-020-00079-4},
  abstract = {Strategic network formation is a branch of network science that takes an economic perspective to the creation of social networks, considering that actors in a network form links in order to maximise some utility that they attain through their connections to other actors in the network. In particular, Jackson's Connections model, writes an actor's utility as a sum over all other actors that can be reached along a path in the network of a benefit value that diminishes with the path length. In this paper, we are interested in the ``social capital'' that an actor retains due to their position in the network. Social capital can be understood as an ability to bond with actors, as well as an ability to form a bridge that connects otherwise disconnected actors. This bridging benefit has previously been modelled in another ``structural hole'' network formation game, proposed by Kleinberg. In this paper, we develop an approach that generalises the utility of Kleinberg's game and combines it with that of the Connections model, to create a utility that models both the bonding and bridging capabilities of an actor with social capital. From this utility and its associated formation game, we derive a new centrality measure, which we dub ``structural hole centrality'', to identify actors with high social capital. We analyse this measure by applying it to networks of different types, and assessing its correlation to other centrality metrics, using a benchmark dataset of 299 networks, drawn from different domains. Finally, using one social network from the dataset, we illustrate how an actor's ``structural hole centrality profile'' can be used to identify their bridging and bonding value to the network.},
  file = {/home/aleksandar/Documents/Zotero/Ghaffar_Hurley/Ghaffar_Hurley_2020_Structural hole centrality.pdf},
  journal = {Computational Social Networks},
  language = {en},
  number = {1}
}

@article{ghezelbashPolarizationCooperativeNetworks2019,
  title = {Polarization in Cooperative Networks through Optimal Placement of Informed Agents},
  author = {Ghezelbash, Ehsan and Yazdanpanah, Mohammad Javad and Asadpour, Masoud},
  year = {2019},
  month = jul,
  pages = {120936},
  issn = {03784371},
  doi = {10.1016/j.physa.2019.04.172},
  journal = {Physica A: Statistical Mechanics and its Applications},
  language = {en}
}

@article{ghoshFractalGaussianNetworks,
  title = {Fractal {{Gaussian Networks}}: {{A}} Sparse Random Graph Model Based on {{Gaussian Multiplicative Chaos}}},
  author = {Ghosh, Subhroshekhar and Balasubramanian, Krishnakumar and Yang, Xiaochuan},
  pages = {16},
  abstract = {We propose a novel stochastic network model, called Fractal Gaussian Network (FGN), that embodies well-defined and analytically tractable fractal structures. Such fractal structures have been empirically observed in diverse applications. FGNs interpolate continuously between the popular purely random geometric graphs (a.k.a. the Poisson Boolean network), and random graphs with increasingly fractal behavior. In fact, they form a parametric family of sparse random geometric graphs that are parametrized by a fractality parameter {$\nu$} which governs the strength of the fractal structure. FGNs are driven by the latent spatial geometry of Gaussian Multiplicative Chaos (GMC), a canonical model of fractality in its own right. We explore the natural question of detecting the presence of fractality and the problem of parameter estimation based on observed network data. Finally, we explore fractality in community structures by unveiling a natural stochastic block model in the setting of FGNs.},
  file = {/home/aleksandar/Zotero/storage/GUKPUHGC/Ghosh et al. - Fractal Gaussian Networks A sparse random graph m.pdf},
  language = {en}
}

@article{giansiracusaComputationalGeometrySupreme,
  title = {Computational Geometry and the {{U}}.{{S}}. {{Supreme Court}}},
  author = {Giansiracusa, Noah and Ricciardi, Cameron},
  doi = {S0165489618300842},
  abstract = {{$<$}p{$>$}Publication date: Available online 2 January 2019{$<$}/p{$><$}p{$>$}\textbf{Source:} Mathematical Social Sciences{$<$}/p{$><$}p{$>$}Author(s): Noah Giansiracusa, Cameron Ricciardi{$<$}/p{$><$}h5{$>$}Abstract{$<$}/h5{$><$}div{$><$}p{$>$}We use the United States Supreme Court as an illuminative context in which to discuss three different spatial voting preference models: an instance of the widely used single-peaked preferences, and two models that are more novel in which vote outcomes have a strength in addition to a location. We introduce each model from a formal axiomatic perspective, briefly discuss practical motivation for each in terms of judicial behavior, prove mathematical relationships among the voting coalitions compatible with each model, and then study the two-dimensional setting by presenting computational tools for working with the models and by exploring these with judicial voting data from the Supreme Court.{$<$}/p{$><$}/div{$>$}},
  journal = {Mathematical Social Science}
}

@article{gierschPunishingCampusProtesters2019,
  title = {Punishing Campus Protesters Based on Ideology},
  author = {Giersch, Jason},
  year = {2019},
  month = oct,
  volume = {6},
  pages = {2053168019892129},
  issn = {2053-1680},
  doi = {10.1177/2053168019892129},
  abstract = {Recent protests on university campuses have inspired conservative claims that liberals allow partisanship to color their judgement of disorderly activists. Prior research suggests, however, that both ideologies are prone to political bias. Furthermore, because conservatives are typically more concerned with orderliness and authority, there are theoretical reasons to expect conservatives to respond more forcefully to protests than liberals, especially when those protesters are political opponents. Using an experimental design with two samples, one with Mechanical Turk participants and the other with current college students, the study finds support for the hypotheses that (1) conservatives are more punitive towards protesters than liberals, (2) both ideologies are more likely to punish when protesters are their political opponents, and (3) conservatives' responses to protesters are more sensitive to their ideology than liberals'. These results support recent studies of the psychology of political ideology and punitiveness.},
  file = {/home/aleksandar/Dropbox/Zotero/Giersch/Giersch_2019_Punishing campus protesters based on ideology.pdf},
  journal = {Research \& Politics},
  language = {en},
  number = {4}
}

@article{gillamBiasedBootstrapSampling,
  title = {Biased Bootstrap Sampling for Efficient Two-Sample Testing.},
  author = {Gillam, Thomas P. S. and Lester, Christopher G.},
  doi = {arXiv:1810.00335v5},
  abstract = {{$<$}p{$>$}The so-called 'energy test' is a frequentist technique used in experimental particle physics to decide whether two samples are drawn from the same distribution. Its usage requires a good understanding of the distribution of the test statistic, T, under the null hypothesis. We propose a technique which allows the extreme tails of the T-distribution to be determined more efficiently than possible with present methods. This allows quick evaluation of (for example) 5-sigma confidence intervals that otherwise would have required prohibitively costly computation times or approximations to have been made. Furthermore, we comment on other ways that T computations could be sped up using established results from the statistics community. Beyond two-sample testing, the proposed biased bootstrap method may provide benefit anywhere extreme values are currently obtained with bootstrap sampling. {$<$}/p{$>$}},
  journal = {arXiv Data Analysis, Statistics and Probability}
}

@article{gillamBiasedBootstrapSamplinga,
  title = {Biased Bootstrap Sampling for Efficient Two-Sample Testing.},
  author = {Gillam, Thomas P. S. and Lester, Christopher G.},
  doi = {arXiv:1810.00335v5},
  abstract = {{$<$}p{$>$}The so-called 'energy test' is a frequentist technique used in experimental particle physics to decide whether two samples are drawn from the same distribution. Its usage requires a good understanding of the distribution of the test statistic, T, under the null hypothesis. We propose a technique which allows the extreme tails of the T-distribution to be determined more efficiently than possible with present methods. This allows quick evaluation of (for example) 5-sigma confidence intervals that otherwise would have required prohibitively costly computation times or approximations to have been made. Furthermore, we comment on other ways that T computations could be sped up using established results from the statistics community. Beyond two-sample testing, the proposed biased bootstrap method may provide benefit anywhere extreme values are currently obtained with bootstrap sampling. {$<$}/p{$>$}},
  journal = {arXiv Data Analysis, Statistics and Probability}
}

@book{gillDemocracyPostcommunismPolitical2002,
  title = {Democracy and Post-Communism: {{Political}} Change in the Post-Communist World},
  shorttitle = {Democracy and Post-Communism},
  author = {Gill, Graeme J.},
  year = {2002},
  publisher = {{Routledge}},
  address = {{London}},
  isbn = {978-0-415-27205-6},
  lccn = {JN96.A58 G54 2002},
  number = {1},
  series = {Routledge Research in Comparative Politics}
}

@article{giniMeasurementInequalityIncomes1921,
  title = {Measurement of Inequality of Incomes},
  author = {Gini, Corrado},
  year = {1921},
  month = mar,
  volume = {31},
  pages = {124},
  issn = {00130133},
  doi = {10.2307/2223319},
  journal = {The Economic Journal},
  number = {121}
}

@article{girvanCommunityStructureSocial2002,
  title = {Community Structure in Social and Biological Networks},
  author = {Girvan, M. and Newman, M. E. J.},
  year = {2002},
  month = jun,
  volume = {99},
  pages = {7821--7826},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.122653799},
  journal = {Proceedings of the National Academy of Sciences},
  language = {en},
  number = {12}
}

@article{giudiceEffectiveDimensionalityTutorial,
  title = {Effective Dimensionality: {{A}} Tutorial},
  author = {Giudice, M Del},
  pages = {30},
  abstract = {The topic of this tutorial is the effective dimensionality (ED) of a dataset, i.e., the equivalent number of orthogonal dimensions that would produce the same overall pattern of covariation. The ED quantifies the total dimensionality of a set of variables, with no assumptions about their underlying structure. The ED of a dataset has important implications for the ``curse of dimensionality;'' it can be used to inform decisions about data analysis and answer meaningful empirical questions. The tutorial offers an accessible introduction to ED, distinguishes it from the related but distinct concept of intrinsic dimensionality (ID), critically reviews various ED estimators, and gives indications for practical use with examples from personality research. An R function is provided to implement the techniques described in the tutorial.},
  file = {/home/aleksandar/Dropbox/Zotero/Giudice/Giudice_Effective dimensionality.pdf;/home/aleksandar/Dropbox/Zotero/Giudice/Giudice_Effective dimensionality2.pdf},
  language = {en}
}

@article{giuntoliExploringDienerMultidimensional2020,
  title = {Exploring {{Diener}}'s {{Multidimensional Conceptualization}} of {{Well}}-{{Being Through Network Psychometrics}}},
  author = {Giuntoli, Laura and Vidotto, Giulio},
  year = {2020},
  month = apr,
  pages = {0033294120916864},
  publisher = {{SAGE Publications Inc}},
  issn = {0033-2941},
  doi = {10.1177/0033294120916864},
  abstract = {Previous research has addressed the study of the well-being structure focusing on the separability among hedonic and eudaimonic dimensions by means of latent variable approaches. Diener's tripartite model of Subjective Well-Being has often been identified with hedonic well-being, while flourishing (i.e., positive functioning) has been classified as a proxy for eudaimonic well-being. Instead of pursuing a theory-driven approach, the structure of well-being dimensions can be retrieved by means of network psychometrics that is a highly informative, data-driven approach that allows the model structure to spontaneously emerge from the relationships among indicators. Furthermore, we propose a strength centrality decomposition that is able to summarize the influence of a specific indicator within its dimension and between the other dimensions. Contrary to the theoretical conjecture that the separability among well-being dimensions can be grounded on a hedonic and eudaimonic distinction, our results point to a categorization of the Diener's well-being indicators based on the type of information they convey, that is global evaluation of life satisfaction, positive and negative affective experiences, and perceived positive functioning in life.},
  journal = {Psychological Reports},
  language = {en}
}

@article{gleesonBranchingProcessDescriptions2020,
  title = {Branching Process Descriptions of Information Cascades on {{Twitter}}},
  author = {Gleeson, James P. and Onaga, Tomokatsu and Fennell, Peter and Cotter, James and Burke, Raymond and O'Sullivan, David J. P.},
  year = {2020},
  month = jul,
  abstract = {A detailed analysis of Twitter-based information cascades is performed, and it is demonstrated that branching process hypotheses are approximately satisfied. Using a branching process framework, models of agent-to-agent transmission are compared to conclude that a limited attention model better reproduces the relevant characteristics of the data than the more common independent cascade model. Existing and new analytical results for branching processes are shown to match well to the important statistical characteristics of the empirical information cascades, thus demonstrating the power of branching process descriptions for understanding social information spreading.},
  archivePrefix = {arXiv},
  eprint = {2007.08916},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/BSRJKHRX/Gleeson et al. - 2020 - Branching process descriptions of information casc.pdf},
  journal = {arXiv:2007.08916 [physics]},
  language = {en},
  primaryClass = {physics}
}

@article{glennTheoreticalEmpiricalConcerns2015,
  title = {Theoretical and {{Empirical Concerns Regarding}} the {{Dark Triad}} as a {{Construct}}},
  author = {Glenn, Andrea L. and Sellbom, Martin},
  year = {2015},
  month = jun,
  volume = {29},
  pages = {360--377},
  issn = {0885-579X},
  doi = {10.1521/pedi_2014_28_162},
  journal = {Journal of Personality Disorders},
  language = {en},
  number = {3}
}

@article{glonekSemisupervisedGraphLabelling,
  title = {Semi-Supervised Graph Labelling Reveals Increasing Partisanship in the {{United States Congress}}. ({{arXiv}}:1904.01153v1 [Cs.{{SI}}])},
  author = {Glonek, Nigel Bean Lewis Mitchell Jonathan Tuke Max},
  doi = {arXiv:1904.01153v1},
  abstract = {Graph labelling is a key activity of network science, with broad practical applications, and close relations to other network science tasks, such as community detection and clustering. While a large body of work exists on both unsupervised and supervised labelling algorithms, the class of random walk-based supervised algorithms requires further exploration, particularly given their relevance to social and political networks. This work refines and expands upon a new semi-supervised graph labelling method, the GLaSS method, that exactly calculates absorption probabilities for random walks on connected graphs. The method models graphs exactly as discrete-time Markov chains, treating labelled nodes as absorbing states. The method is applied to roll call voting data for 42 meetings of the United States House of Representatives and Senate, from 1935 to 2019. Analysis of the 84 resultant political networks demonstrates strong and consistent performance of GLaSS when estimating labels for unlabelled nodes in graphs, and reveals a significant trend of increasing partisanship within the United States Congress.},
  journal = {arXiv Physics and Society}
}

@article{glonekSemisupervisedGraphLabellinga,
  title = {Semi-Supervised Graph Labelling Reveals Increasing Partisanship in the {{United States Congress}}. ({{arXiv}}:1904.01153v1 [Cs.{{SI}}])},
  author = {Glonek, Nigel Bean Lewis Mitchell Jonathan Tuke Max},
  doi = {arXiv:1904.01153v1},
  abstract = {Graph labelling is a key activity of network science, with broad practical applications, and close relations to other network science tasks, such as community detection and clustering. While a large body of work exists on both unsupervised and supervised labelling algorithms, the class of random walk-based supervised algorithms requires further exploration, particularly given their relevance to social and political networks. This work refines and expands upon a new semi-supervised graph labelling method, the GLaSS method, that exactly calculates absorption probabilities for random walks on connected graphs. The method models graphs exactly as discrete-time Markov chains, treating labelled nodes as absorbing states. The method is applied to roll call voting data for 42 meetings of the United States House of Representatives and Senate, from 1935 to 2019. Analysis of the 84 resultant political networks demonstrates strong and consistent performance of GLaSS when estimating labels for unlabelled nodes in graphs, and reveals a significant trend of increasing partisanship within the United States Congress.},
  journal = {arXiv Physics and Society}
}

@book{gloppenGlobalizationDemocratizationChallenges2007,
  title = {Globalization and Democratization: {{Challenges}} for Political Parties},
  shorttitle = {Globalization and Democratization},
  editor = {Gloppen, Siri and Sv{\textdegree}asand, Lars},
  year = {2007},
  publisher = {{Fagbokforlaget}},
  address = {{Bergen}},
  annotation = {OCLC: 485469846},
  isbn = {978-82-450-0694-0},
  language = {eng}
}

@book{goatiPartijePartijskiSistemi2004,
  title = {Partije i Partijski Sistemi u {{Srbiji}}},
  author = {Goati, V.},
  year = {2004},
  publisher = {{Odbor za gra\dj ansku inicijativu}},
  address = {{Ni\v{s}}}
}

@article{goelModellingCompetitiveMarketing,
  title = {Modelling Competitive Marketing Strategies in Social Networks},
  author = {Goel, Rahul and Singh, Anurag and Ghanbarnejad, Fakhteh},
  doi = {S0378437118314523},
  abstract = {{$<$}p{$>$}Publication date: Available online 27 November 2018{$<$}/p{$><$}p{$>$}\textbf{Source:} Physica A: Statistical Mechanics and its Applications{$<$}/p{$><$}p{$>$}Author(s): Rahul Goel, Anurag Singh, Fakhteh Ghanbarnejad{$<$}/p{$><$}h5{$>$}Abstract{$<$}/h5{$><$}div{$><$}p{$>$}A model is developed in which two players compete to spread information in the large network. Players choose their initial seed nodes simultaneously and the information is diffused according to Independent Cascade model (ICM). The main aim of the player is to choose the seed nodes such that they will spread its information to as many nodes as possible in a social network. Here we show and discuss how the rate of spreading of information as well as seed choosing depending on topological features play roles in information diffusion process. Any node in a social network will get influenced by none or one or more than one information. We also analyzed how much fraction of nodes in different compartment changes by changing the rate of spreading of information. Finally, a game theory model is developed to obtain the Nash equilibrium based on best response function of the players. This model is based on Hotelling's model of electoral competition.{$<$}/p{$><$}/div{$>$}},
  journal = {Physica A: Statistical Mechanics and its Applications}
}

@article{goelModellingCompetitiveMarketinga,
  title = {Modelling Competitive Marketing Strategies in Social Networks},
  author = {Goel, Rahul and Singh, Anurag and Ghanbarnejad, Fakhteh},
  doi = {S0378437118314523},
  abstract = {{$<$}p{$>$}Publication date: Available online 27 November 2018{$<$}/p{$><$}p{$>$}\textbf{Source:} Physica A: Statistical Mechanics and its Applications{$<$}/p{$><$}p{$>$}Author(s): Rahul Goel, Anurag Singh, Fakhteh Ghanbarnejad{$<$}/p{$><$}h5{$>$}Abstract{$<$}/h5{$><$}div{$><$}p{$>$}A model is developed in which two players compete to spread information in the large network. Players choose their initial seed nodes simultaneously and the information is diffused according to Independent Cascade model (ICM). The main aim of the player is to choose the seed nodes such that they will spread its information to as many nodes as possible in a social network. Here we show and discuss how the rate of spreading of information as well as seed choosing depending on topological features play roles in information diffusion process. Any node in a social network will get influenced by none or one or more than one information. We also analyzed how much fraction of nodes in different compartment changes by changing the rate of spreading of information. Finally, a game theory model is developed to obtain the Nash equilibrium based on best response function of the players. This model is based on Hotelling's model of electoral competition.{$<$}/p{$><$}/div{$>$}},
  journal = {Physica A: Statistical Mechanics and its Applications}
}

@inproceedings{golbeckComputingApplyingTrust2005,
  title = {Computing and {{Applying Trust}} in {{Web}}-Based {{Social Networks}}},
  author = {Golbeck, J.},
  year = {2005},
  abstract = {The proliferation of web-based social networks has lead to new innovations in social networking, particularly by allowing users to describe their relationships beyond a basic connection. In this dissertation, I look specifically at trust in web-based social networks, how it can be computed, and how it can be used in applications. I begin with a definition of trust and a description of several properties that affect how it is used in algorithms. This is complemented by a survey of web-based social networks to gain an understanding of their scope, the types of relationship information available, and the current state of trust.  The computational problem of trust is to determine how much one person in the network should trust another person to whom they are not connected. I present two sets of algorithms for calculating these trust inferences: one for networks with binary trust ratings, and one for continuous ratings. For each rating scheme, the algorithms are built upon the defined notions of trust. Each is then analyzed theoretically and with respect to simulated and actual trust networks to determine how accurately they calculate the opinions of people in the system. I show that in both rating schemes the algorithms presented can be expected to be quite accurate.  These calculations are then put to use in two applications. FilmTrust is a website that combines trust, social networks, and movie ratings and reviews. Trust is used to personalize the website for each user, displaying recommended movie ratings, and ordering reviews by relevance. I show that, in the case where the user's opinion is divergent from the average, the trust-based recommended ratings are more accurate than several other common collaborative filtering techniques. The second application is TrustMail, an email client that uses the trust rating of each sender as a score for the message. Users can then sort messages according to their trust value.  I conclude with a description of other applications where trust inferences can be used, and how the lessons from this dissertation can be applied to infer information about relationships in other complex systems.}
}

@article{goldbergEvolutionCleavageVoting,
  title = {The Evolution of Cleavage Voting in Four {{Western}} Countries: {{Structural}}, Behavioural or Political Dealignment?},
  author = {GOLDBERG, ANDREAS C.},
  doi = {10.1111/1475-6765.12336},
  abstract = {Since the heyday of cleavage voting in the 1960s and 1970s, the majority of studies presents evidence of a decline in cleavage voting \textendash{} caused by either structural or behavioural dealignment. Structural dealignment denotes changes in group size responsible for a decrease in cleavage voting, whereas behavioural dealignment concerns weakening party\textendash voter links over time. A third phenomenon posited in this article is the collective voting abstention of certain (social) groups, here referred to as 'political dealignment', which results in a new type of division of voting versus abstention. The purpose of this article is to examine the three underlying mechanisms for the decline in social class and religious cleavage voting across four Western countries (Great Britain, the Netherlands, Switzerland and the United States) over the last 40\textendash 60 years using longitudinal post-election data. The results prove a strong presence of political dealignment and increasing turnout gaps regarding both the class and religious cleavage. Furthermore, whenever a decline in cleavage voting is present, it is mainly caused by changes in the social groups' behaviour and less by changing social structures in a country.},
  journal = {European Journal of Political Research}
}

@article{goldbergEvolutionCleavageVoting2020,
  title = {The Evolution of Cleavage Voting in Four {{Western}} Countries: {{Structural}}, Behavioural or Political Dealignment?},
  shorttitle = {The Evolution of Cleavage Voting in Four {{Western}} Countries},
  author = {Goldberg, Andreas C.},
  year = {2020},
  month = feb,
  volume = {59},
  pages = {68--90},
  issn = {0304-4130, 1475-6765},
  doi = {10.1111/1475-6765.12336},
  file = {/home/aleksandar/Documents/Zotero/Goldberg/Goldberg_2020_The evolution of cleavage voting in four Western countries.pdf},
  journal = {European Journal of Political Research},
  language = {en},
  number = {1}
}

@article{goldbergEvolutionCleavageVotinga,
  title = {The Evolution of Cleavage Voting in Four {{Western}} Countries: {{Structural}}, Behavioural or Political Dealignment?},
  author = {GOLDBERG, ANDREAS C.},
  doi = {10.1111/1475-6765.12336},
  abstract = {Since the heyday of cleavage voting in the 1960s and 1970s, the majority of studies presents evidence of a decline in cleavage voting \textendash{} caused by either structural or behavioural dealignment. Structural dealignment denotes changes in group size responsible for a decrease in cleavage voting, whereas behavioural dealignment concerns weakening party\textendash voter links over time. A third phenomenon posited in this article is the collective voting abstention of certain (social) groups, here referred to as 'political dealignment', which results in a new type of division of voting versus abstention. The purpose of this article is to examine the three underlying mechanisms for the decline in social class and religious cleavage voting across four Western countries (Great Britain, the Netherlands, Switzerland and the United States) over the last 40\textendash 60 years using longitudinal post-election data. The results prove a strong presence of political dealignment and increasing turnout gaps regarding both the class and religious cleavage. Furthermore, whenever a decline in cleavage voting is present, it is mainly caused by changes in the social groups' behaviour and less by changing social structures in a country.},
  journal = {European Journal of Political Research}
}

@article{goldbergMobilizingDifferentTypes,
  ids = {goldbergMobilizingDifferentTypesa},
  title = {Mobilizing Different Types of Voters: {{The}} Influence of Campaign Intensity on Turnout in Direct Democratic Votes},
  author = {Goldberg, Andreas C. and Lanz, Simon and Sciarini, Pascal},
  doi = {S0261379418301306},
  abstract = {{$<$}p{$>$}Publication date: Available online 6 December 2018{$<$}/p{$><$}p{$>$}\textbf{Source:} Electoral Studies{$<$}/p{$><$}p{$>$}Author(s): Andreas C. Goldberg, Simon Lanz, Pascal Sciarini{$<$}/p{$><$}div xml:lang="en"{$><$}h5{$>$}Abstract{$<$}/h5{$><$}div{$><$}p{$>$}A well-established body of literature links voter turnout to political campaigns. In this view, intensive campaigns increase the perceived salience of a decision, fostering information-seeking and, ultimately, turnout. The existing literature has also advanced our understanding of how direct democratic institutions influence turnout in elections. Yet we still know little about whether and to what extent campaign efforts influence voter turnout in direct democratic votes, and we know even less about who is mobilized. We claim that campaign intensity has differentiated effects across voters, depending on voters' participation profile. To test this claim we use a rich dataset of official turnout data covering more than 40 direct democratic votes in Switzerland. The results support our claim. While intensive political campaigns overall foster citizens to turn out to vote, they do so especially for ``selective'' (or ``intermittent'') voters, who need to decide anew at each ballot whether to turn out or not. Interestingly, we also find that frequent abstainers are not immune from campaign effects, and get almost as strongly mobilized as selective voters in highly intensive campaigns.{$<$}/p{$><$}/div{$><$}/div{$>$}},
  journal = {Electoral Studies}
}

@techreport{golinoEntropyFitIndices2019,
  title = {Entropy {{Fit Indices}}: {{New Fit Measures}} for {{Assessing}} the {{Structure}} and {{Dimensionality}} of {{Multiple Latent Variables}}.},
  shorttitle = {Entropy {{Fit Indices}}},
  author = {Golino, Hudson and Moulder, Robert Glenn and Shi, Dingjing and Christensen, Alexander P. and Garrido, Luis E. and Nieto, Maria Dolores and Nesselroade, John R. and Sadana, Ritu and Thiyagarajan, Jotheeswaran Amuthavalli and Boker, Steven M.},
  year = {2019},
  month = sep,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/mtka2},
  abstract = {The accurate identification of the content and number of latent factors underlying multivariate data is an important endeavor in many areas of Psychology and related fields. Recently, a new dimensionality assessment technique based on network psychometrics was proposed (Exploratory Graph Analysis, EGA), but a measure to check the fit of the dimensionality structure to the data estimated via EGA is still lacking. Although traditional factor-analytic fit measures are widespread, recent research has identified limitations for their effectiveness in categorical variables. Here, we propose three new fit measures (termed entropy fit indices) that combines information theory, quantum information theory and structural analysis: Entropy Fit Index (EFI), EFI with Von Neumman Entropy (EFI.vn) and Total EFI.vn (TEFI.vn). The first can be estimated in complete datasets using Shannon entropy, while EFI.vn and TEFI.vn can be estimated in correlation matrices using quantum information metrics. We show, through several simulations, that TEFI.vn, EFI.vn and EFI are as accurate or more accurate than traditional fit measures when identifying the number of simulated latent factors. However, in conditions where more factors are extracted than the number of factors simulated, only TEFI.vn presents a very high accuracy. In addition, we provide an applied example that demonstrates how the new fit measures can be used with a real-world dataset, using exploratory graph analysis.},
  annotation = {cites: golinoEntropyFitIndices2019},
  file = {/home/aleksandar/Zotero/storage/CAA9KWQ8/Golino et al_2019_Entropy Fit Indices.pdf},
  keywords = {TODO},
  language = {en},
  type = {Preprint}
}

@article{golinoExploratoryGraphAnalysis2017,
  title = {Exploratory Graph Analysis: {{A}} New Approach for Estimating the Number of Dimensions in Psychological Research},
  shorttitle = {Exploratory Graph Analysis},
  author = {Golino, Hudson F. and Epskamp, Sacha},
  year = {2017},
  month = jun,
  volume = {12},
  pages = {e0174035},
  publisher = {{Public Library of Science}},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0174035},
  abstract = {The estimation of the correct number of dimensions is a long-standing problem in psychometrics. Several methods have been proposed, such as parallel analysis (PA), Kaiser-Guttman's eigenvalue-greater-than-one rule, multiple average partial procedure (MAP), the maximum-likelihood approaches that use fit indexes as BIC and EBIC and the less used and studied approach called very simple structure (VSS). In the present paper a new approach to estimate the number of dimensions will be introduced and compared via simulation to the traditional techniques pointed above. The approach proposed in the current paper is called exploratory graph analysis (EGA), since it is based on the graphical lasso with the regularization parameter specified using EBIC. The number of dimensions is verified using the walktrap, a random walk algorithm used to identify communities in networks. In total, 32,000 data sets were simulated to fit known factor structures, with the data sets varying across different criteria: number of factors (2 and 4), number of items (5 and 10), sample size (100, 500, 1000 and 5000) and correlation between factors (orthogonal, .20, .50 and .70), resulting in 64 different conditions. For each condition, 500 data sets were simulated using lavaan. The result shows that the EGA performs comparable to parallel analysis, EBIC, eBIC and to Kaiser-Guttman rule in a number of situations, especially when the number of factors was two. However, EGA was the only technique able to correctly estimate the number of dimensions in the four-factor structure when the correlation between factors were .7, showing an accuracy of 100\% for a sample size of 5,000 observations. Finally, the EGA was used to estimate the number of factors in a real dataset, in order to compare its performance with the other six techniques tested in the simulation study.},
  file = {/home/aleksandar/Zotero/storage/XY8Z3FDD/Golino_Epskamp_2017_Exploratory graph analysis.pdf;/home/aleksandar/Zotero/storage/GT5J5KPP/article.html;/home/aleksandar/Zotero/storage/K8C5JCIY/article.html},
  journal = {PLOS ONE},
  keywords = {Covariance,Developmental psychology,Eigenvalues,Factor analysis,Network analysis,Psychology,Psychometrics,Simulation and modeling},
  language = {en},
  number = {6}
}

@article{golinoInvestigatingPerformanceExploratory2020,
  title = {Investigating the Performance of Exploratory Graph Analysis and Traditional Techniques to Identify the Number of Latent Factors: {{A}} Simulation and Tutorial},
  shorttitle = {Investigating the Performance of Exploratory Graph Analysis and Traditional Techniques to Identify the Number of Latent Factors},
  author = {Golino, Hudson and Shi, Dingjing and Christensen, Alexander P. and Garrido, Luis Eduardo and Nieto, Maria Dolores and Sadana, Ritu and Thiyagarajan, Jotheeswaran Amuthavalli and {Martinez-Molina}, Agustin},
  year = {2020},
  pages = {No Pagination Specified-No Pagination Specified},
  publisher = {{American Psychological Association}},
  address = {{US}},
  issn = {1939-1463(Electronic),1082-989X(Print)},
  doi = {10.1037/met0000255},
  abstract = {Exploratory graph analysis (EGA) is a new technique that was recently proposed within the framework of network psychometrics to estimate the number of factors underlying multivariate data. Unlike other methods, EGA produces a visual guide\textemdash network plot\textemdash that not only indicates the number of dimensions to retain, but also which items cluster together and their level of association. Although previous studies have found EGA to be superior to traditional methods, they are limited in the conditions considered. These issues are addressed through an extensive simulation study that incorporates a wide range of plausible structures that may be found in practice, including continuous and dichotomous data, and unidimensional and multidimensional structures. Additionally, two new EGA techniques are presented: one that extends EGA to also deal with unidimensional structures, and the other based on the triangulated maximally filtered graph approach (EGAtmfg). Both EGA techniques are compared with 5 widely used factor analytic techniques. Overall, EGA and EGAtmfg are found to perform as well as the most accurate traditional method, parallel analysis, and to produce the best large-sample properties of all the methods evaluated. To facilitate the use and application of EGA, we present a straightforward R tutorial on how to apply and interpret EGA, using scores from a well-known psychological instrument: the Marlowe-Crowne Social Desirability Scale. (PsycINFO Database Record (c) 2020 APA, all rights reserved)},
  journal = {Psychological Methods}
}

@article{golinoInvestigatingPerformanceExploratory2020a,
  title = {Investigating the Performance of Exploratory Graph Analysis and Traditional Techniques to Identify the Number of Latent Factors: {{A}} Simulation and Tutorial},
  shorttitle = {Investigating the Performance of Exploratory Graph Analysis and Traditional Techniques to Identify the Number of Latent Factors},
  author = {Golino, Hudson and Shi, Dingjing and Christensen, Alexander P. and Garrido, Luis Eduardo and Nieto, Maria Dolores and Sadana, Ritu and Thiyagarajan, Jotheeswaran Amuthavalli and {Martinez-Molina}, Agustin},
  year = {2020},
  volume = {25},
  pages = {292--320},
  publisher = {{American Psychological Association}},
  address = {{US}},
  issn = {1939-1463(Electronic),1082-989X(Print)},
  doi = {10.1037/met0000255},
  abstract = {Exploratory graph analysis (EGA) is a new technique that was recently proposed within the framework of network psychometrics to estimate the number of factors underlying multivariate data. Unlike other methods, EGA produces a visual guide\textemdash network plot\textemdash that not only indicates the number of dimensions to retain, but also which items cluster together and their level of association. Although previous studies have found EGA to be superior to traditional methods, they are limited in the conditions considered. These issues are addressed through an extensive simulation study that incorporates a wide range of plausible structures that may be found in practice, including continuous and dichotomous data, and unidimensional and multidimensional structures. Additionally, two new EGA techniques are presented: one that extends EGA to also deal with unidimensional structures, and the other based on the triangulated maximally filtered graph approach (EGAtmfg). Both EGA techniques are compared with 5 widely used factor analytic techniques. Overall, EGA and EGAtmfg are found to perform as well as the most accurate traditional method, parallel analysis, and to produce the best large-sample properties of all the methods evaluated. To facilitate the use and application of EGA, we present a straightforward R tutorial on how to apply and interpret EGA, using scores from a well-known psychological instrument: the Marlowe-Crowne Social Desirability Scale. (PsycInfo Database Record (c) 2020 APA, all rights reserved)},
  file = {/home/aleksandar/Zotero/storage/8FSWP3VZ/Golino et al_2020_Investigating the performance of exploratory graph analysis and traditional.pdf;/home/aleksandar/Zotero/storage/QV4729B2/2020-19298-001.html;/home/aleksandar/Zotero/storage/YEQR7LVJ/2020-19298-001.html},
  journal = {Psychological Methods},
  keywords = {Exploratory Factor Analysis,Factor Analysis,Psychometrics,Simulation,Social Desirability,TODO},
  number = {3}
}

@techreport{golinoModelingLatentTopics2020,
  title = {Modeling Latent Topics in Social Media Using {{Dynamic Exploratory Graph Analysis}}: {{The}} Case of the Right-Wing and Left-Wing Trolls in the 2016 {{US}} Elections},
  shorttitle = {Modeling Latent Topics in Social Media Using {{Dynamic Exploratory Graph Analysis}}},
  author = {Golino, Hudson and Christensen, Alexander P. and Moulder, Robert Glenn and Kim, Seohyun and Boker, Steven M.},
  year = {2020},
  month = apr,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/tfs7c},
  abstract = {The past few years were marked by increased online offensive strategies perpetrated by state and non-state actors to promote their political agenda, sow discord and question the legitimacy of democratic institutions in the US and Western Europe. In 2016 the US congress identified a list of Russian state-sponsored Twitter accounts that were used to try to divide voters on a wide range of issues. Previous research used Latent Dirichlet Allocation (LDA) to estimate latent topics in data extracted from these accounts. Howerver, LDA is has characteristics that may pose significant limitations to be used in data from social media: the number of latent topics must be specified by the user, interpretability can be difficult to achieve, and it doesn't model short-term temporal dynamics. In the current paper we propose a new method to estimate latent topics in texts from social media termed Dynamic Exploratory Graph Analysis (DynEGA). We compare DynEGA and LDA in a Monte-Carlo simulation in terms of their capacity to estimate the number of simulated latent topics. Finally, we apply the DynEGA method to a large dataset with Twitter posts from state-sponsored right- and left-wing trolls during the 2016 US presidential election. The results show that DynEGA is substantially more accurate to estimate the number of simulated topics than several different LDA algorithms. Our empirical example shows that DynEGA revealed topics that were pertinent to several consequential events in the election cycle, demonstrating the coordinated effort of trolls capitalizing on current events in the U.S. This demonstrates the potential power of our approach for revealing temporally relevant information from qualitative text data.},
  file = {/home/aleksandar/Dropbox/Zotero/Golino et al/Golino et al_2020_Modeling latent topics in social media using Dynamic Exploratory Graph Analysis.pdf},
  language = {en},
  type = {Preprint}
}

@article{golosovElectoralSystemsTerritorial2016,
  title = {Electoral {{Systems}} and {{Territorial Representation}}},
  author = {Golosov, Grigorii V.},
  year = {2016},
  month = jul,
  volume = {52},
  pages = {119--134},
  issn = {0034-4893, 1749-4001},
  doi = {10.1080/00344893.2017.1287771},
  journal = {Representation},
  language = {en},
  number = {2-3}
}

@article{gomersallComplexAdaptiveSystems2018,
  title = {Complex Adaptive Systems: A New Approach for Understanding Health Practices},
  shorttitle = {Complex Adaptive Systems},
  author = {Gomersall, Tim},
  year = {2018},
  month = oct,
  volume = {12},
  pages = {405--418},
  publisher = {{Routledge}},
  issn = {1743-7199},
  doi = {10.1080/17437199.2018.1488603},
  abstract = {This article explores the potential of complex adaptive systems (CAS) theory to inform behaviour change research. A CAS describes a collection of heterogeneous agents interacting within a particular context, adapting to each other's actions. In practical terms, this implies that behaviour change is (1) socially and culturally situated; (2) highly sensitive to small baseline differences in individuals, groups, and intervention components; and (3) determined by multiple components interacting `chaotically'. Two approaches to studying CAS are briefly reviewed. Agent-based modelling is a computer simulation technique that allows researchers to investigate `what if' questions in a virtual environment. Applied qualitative research techniques, on the other hand, offer a way to examine what happens when an intervention is pursued in real-time, and to identify the sorts of rules and assumptions governing social action. Although these represent very different approaches to complexity, there may be scope for mixing these methods \textendash{} for example, by grounding models in insights derived from qualitative fieldwork. Finally, I will argue that the concept of CAS offers one opportunity to gain a deepened understanding of health-related practices, and to examine the social psychological processes that produce health-promoting or damaging actions.},
  annotation = {\_eprint: https://doi.org/10.1080/17437199.2018.1488603},
  file = {/home/aleksandar/Dropbox/Zotero/Gomersall/Gomersall_2018_Complex adaptive systems.pdf;/home/aleksandar/Zotero/storage/3CUU8IRI/17437199.2018.html;/home/aleksandar/Zotero/storage/5BIQB78Q/17437199.2018.html},
  journal = {Health Psychology Review},
  keywords = {Agent-based modelling,behaviour change,complex adaptive systems,health behaviour,qualitative research,social networks},
  number = {4},
  pmid = {29932851}
}

@article{gomezpenedoComplexInterplayPain2020,
  title = {The {{Complex Interplay}} of {{Pain}}, {{Depression}}, and {{Anxiety Symptoms}} in {{Patients With Chronic Pain}}: {{A Network Approach}}},
  shorttitle = {The {{Complex Interplay}} of {{Pain}}, {{Depression}}, and {{Anxiety Symptoms}} in {{Patients With Chronic Pain}}},
  author = {G{\'o}mez Penedo, Juan M. and Rubel, Julian A. and Bl{\"a}ttler, Larissa and Schmidt, Stefanie J. and Stewart, Julian and Egloff, Niklaus and {grosse Holtforth}, Martin},
  year = {2020},
  month = apr,
  volume = {36},
  pages = {249--259},
  issn = {0749-8047},
  doi = {10.1097/AJP.0000000000000797},
  abstract = {Objective:~This study aimed to analyze the associations among depressive and anxiety and pain symptoms in patients diagnosed with chronic pain.         Materials and Methods:~Four hundred fifty-four inpatients who were consecutively admitted in a multimodal 3-week treatment in a tertiary, psychosomatic university clinic completed 25 items from the Brief Pain Inventory and the Hospital Anxiety and Depression Scale at baseline and after treatment termination. Associations among symptoms were explored by network analyses using the graphical least absolute shrinkage and selection operator to estimate their partial correlations, whereas Extended Bayesian Information Criterion was used to select the best network solution for the data. We explored symptoms' centrality and expected influence within the network and the minimum spanning tree for the network.         Results:~Besides expected associations within depressive and anxiety and pain symptoms, the estimated network showed several local associations between depressive and pain interference symptoms. The lacks of being cheerful and of laughing are 2 of the depressive symptoms that showed the greatest associations with pain interference and a strong centrality within the network. Sleep problems were associated with both anxiety and depressive symptoms and pain intensity symptoms. Although at posttreatment most of the symptoms showed a significant decrease, the strength of the associations between the symptoms within the network was significantly higher than at baseline.         Discussion:~The results support focusing psychosocial interventions in chronic pain treatment not only on reducing pain, anxiety, and sleep symptoms but also on enhancing positive affect. Future research is needed to replicate these findings using repeated within-person measures designs.},
  file = {/home/aleksandar/Zotero/storage/5CLM5J2M/The_Complex_Interplay_of_Pain,_Depression,_and.3.html},
  journal = {The Clinical Journal of Pain},
  language = {en-US},
  number = {4}
}

@article{gongMeasuringNetworkRationality2021,
  title = {Measuring Network Rationality and Simulating Information Diffusion Based on Network Structure},
  author = {Gong, Hao and Guo, Chunxiang and Liu, Yu},
  year = {2021},
  month = feb,
  volume = {564},
  pages = {125501},
  issn = {0378-4371},
  doi = {10.1016/j.physa.2020.125501},
  abstract = {The absence of rationality in online public discussions leads to many negative problems, such as cyber violence, which often causes serious psychological harm to the people involved in public opinions. The participants in online discussions constitute a complex network system; however, until now, there are few studies that have proposed a definition and measurement of network rationality from a systematic perspective, which makes us unable to assess the rationality of a network reasonably. In this paper, we propose a definition and measurement of network rationality. Then, we build a model based on the fraction of rational nodes and homophily to simulate the generation of social networks, and we reveal their influence on network rationality and irrational information diffusion on a network. Our preliminary results show that a network with higher rationality will create a ''virtuous circle'' more easily than a network with lower rationality, even if they have exactly the same initial number of rational nodes. In addition, the higher the rationality of a network is, the weaker the influence of the irrational information on the network will be.},
  file = {/home/aleksandar/Zotero/storage/N88R3QUV/S0378437120307998.html},
  journal = {Physica A: Statistical Mechanics and its Applications},
  keywords = {Cyber violence,Homophily,Information diffusion,Irrational information,Network rationality},
  language = {en}
}

@article{gonultasSocialDevelopmentalPerspectiveIntergroup2019,
  title = {Social-{{Developmental Perspective}} on {{Intergroup Attitudes}} towards {{Immigrants}} and {{Refugees}} in {{Childhood}} and {{Adolescence}}: {{A Roadmap}} from {{Theory}} to {{Practice}} for an {{Inclusive Society}}},
  shorttitle = {Social-{{Developmental Perspective}} on {{Intergroup Attitudes}} towards {{Immigrants}} and {{Refugees}} in {{Childhood}} and {{Adolescence}}},
  author = {G{\"o}n{\"u}lta{\c s}, Se{\c c}il and Mulvey, Kelly Lynn},
  year = {2019},
  volume = {63},
  pages = {90--111},
  issn = {0018-716X, 1423-0054},
  doi = {10.1159/000503173},
  abstract = {The unprecedented rates of migration throughout the world have raised concerns about the social integration of immigrants and refugees due to possible experiences of prejudice, discrimination, and hostility from members of the host society. In this article, we review developmental and social theories and related research outlining children's and adolescents' intergroup attitudes towards immigrants and refugees. The discussion then moves to social agents that help shape children's and adolescents' attitudes regarding these relations. Theory-driven, empirically tested intervention studies that could potentially promote children's and adolescents' attitudes towards immigrants and refugees are discussed. We also address the limitations of current interventions, which were the starting points for this paper. Finally, we highlight important avenues for future research and make specific recommendations for practitioners and policy makers striving to promote harmonious intergroup relations across childhood and adolescence in social settings.},
  file = {/home/aleksandar/Zotero/storage/ZX45SJU3/503173.html},
  journal = {Human Development},
  language = {english},
  number = {2}
}

@book{goodchildSpatiallyIntegratedSocial2004,
  title = {Spatially Integrated Social Science},
  editor = {Goodchild, Michael F. and Janelle, Donald G.},
  year = {2004},
  publisher = {{Oxford University Press}},
  address = {{Oxford}},
  isbn = {978-0-19-515270-8},
  lccn = {HA30.6 .S665 2004},
  series = {Spatial Information Systems}
}

@article{gordonIndividualPreferencesGrowth2020,
  title = {Individual {{Preferences}} and the {{Growth Dynamics}} of {{Two Political Parties}}: {{Insights}} through a {{Simple Mathematical Model}}},
  shorttitle = {Individual {{Preferences}} and the {{Growth Dynamics}} of {{Two Political Parties}}},
  author = {Gordon, Joseph and Nyabadza, Farai},
  year = {2020},
  month = sep,
  volume = {9},
  pages = {7},
  abstract = {Formation and the change of individual preferences from one political party to the other has now become a common trend in most democratic countries. Many party principles and as a result change their respective parties. This project work developed and analyzed the use of non-linear mathematical model for the spread of two political  parties, the ruling party and the opposition. We used principles borrowed from infectious diseases modeling to track the changes of the membership of each political party taking into consideration preferences. The whole population was assumed to be constant and homogeneously mixed. Steady states were analytically obtained and their stability nature discussed. Conditions for the existence of single parties and the existence of both parties were obtained. Numerical simulations were also performed to support the analytical results. This study has a potential to enrich political dynamics as nations embrace democratic principles.},
  journal = {Journal of Applied \& Computational Mathematics}
}

@article{gorenHumanValuesSophistication2020,
  ids = {gorenHumanValuesSophistication2020a},
  title = {Human {{Values}} and {{Sophistication Interaction Theory}}},
  author = {Goren, Paul and Smith, Brianna and Motta, Matthew},
  year = {2020},
  month = may,
  issn = {1573-6687},
  doi = {10.1007/s11109-020-09611-8},
  abstract = {Political sophistication systematically affects the structure, crystallization, and use of political values, but it remains unclear if sophistication manifests similar effects on human values. This paper integrates Shalom Schwartz (Adv Exp Soc Psychol 25:1\textendash 65, 1992, J Soc Issues 50:19\textendash 45, 1994) theory of human values with sophistication interaction theory to examine the degree to which education and political interest condition the structure, crystallization, and use of an important subset of values. We theorize that human values are (1) identically structured and equally crystallized in sophistication-stratified populations and (2) that relationships between human values and ideological judgments grow stronger at higher levels of sophistication. Using data from a nationally representative sample of 10,765 Americans, we compare extremely sophisticated individuals (e.g., people with doctorates) and extremely unsophisticated individuals (e.g., high school dropouts) to demonstrate that neither education nor political interest affect value structure and crystallization. Sophistication has real, if somewhat limited, effects on value usage.},
  file = {/home/aleksandar/Dropbox/Zotero/Goren et al/Goren et al_2020_Human Values and Sophistication Interaction Theory.pdf},
  journal = {Political Behavior},
  language = {en}
}

@article{gotoDiscriminantAnalysisBased,
  ids = {gotoDiscriminantAnalysisBaseda},
  title = {Discriminant Analysis Based on Binary Time Series},
  author = {Goto, Yuichi and Taniguchi, Masanobu},
  doi = {10.1007/s00184-019-00746-1},
  abstract = {Binary time series can be derived from an underlying latent process. In this paper, we consider an ellipsoidal alpha mixing strictly stationary process and discuss the discriminant analysis and propose a classification method based on binary time series. Assume that the observations are generated by time series which belongs to one of two categories described by different spectra. We propose a method to classify into the correct category with high probability. First, we will show that the misclassification probability tends to zero when the number of observation tends to infinity, that is, the consistency of our discrimination method. Further, we evaluate the asymptotic misclassification probability when the two categories are contiguous. Finally, we show that our classification method based on binary time series has good robustness properties when the process is contaminated by an outlier, that is, our classification method is insensitive to the outlier. However, the classical method based on smoothed periodogram is sensitive to outliers. We also deal with a practical case where the two categories are estimated from the training samples. For an electrocardiogram data set, we examine the robustness of our method when observations are contaminated with an outlier.},
  journal = {Metrika}
}

@book{gowersPrincetonCompanionMathematics2008,
  title = {The {{Princeton}} Companion to Mathematics},
  editor = {Gowers, Timothy and {Barrow-Green}, June and Leader, Imre and Princeton University},
  year = {2008},
  publisher = {{Princeton University Press}},
  address = {{Princeton}},
  isbn = {978-0-691-11880-2},
  lccn = {QA11.2 .P745 2008}
}

@article{grabischDiffusionLargeNetworks2020,
  title = {Diffusion in Large Networks},
  author = {Grabisch, Michel and Rusinowska, Agnieszka and Venel, Xavier},
  year = {2020},
  month = oct,
  abstract = {We investigate the phenomenon of diffusion in a countably infinite society of individuals interacting with their neighbors in a network. At a given time, each individual is either active or inactive. The diffusion is driven by two characteristics: the network structure and the diffusion mechanism represented by an aggregation function. We distinguish between two diffusion mechanisms (probabilistic, deterministic) and focus on two types of aggregation functions (strict, Boolean). Under strict aggregation functions, polarization of the society cannot happen, and its state evolves towards a mixture of infinitely many active and infinitely many inactive agents, or towards a homogeneous society. Under Boolean aggregation functions, the diffusion process becomes deterministic and the contagion model of Morris (2000) becomes a particular case of our framework. Polarization can then happen. Our dynamics also allows for cycles in both cases. The network structure is not relevant for these questions, but is important for establishing irreducibility, at the price of a richness assumption: the network should contain infinitely many complex stars and have enough space for storing local configurations. Our model can be given a game-theoretic interpretation via a local coordination game, where each player would apply a best-response strategy in a random neighborhood.},
  archivePrefix = {arXiv},
  eprint = {2010.09256},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Grabisch et al/Grabisch et al_2020_Diffusion in large networks.pdf;/home/aleksandar/Zotero/storage/SVA8BX5G/2010.html},
  journal = {arXiv:2010.09256 [cs]},
  primaryClass = {cs}
}

@article{grafsteinProblemPolarization,
  title = {The Problem of Polarization},
  author = {Grafstein, Robert},
  doi = {10.1007/s11127-018-0547-z},
  abstract = {{$<$}h3 class="a-plus-plus"{$>$}Abstract{$<$}/h3{$>$}                     {$<$}p class="a-plus-plus"{$>$}This paper offers a unified political economy explanation of political extremism and moderation regarding income redistribution. Unlike the standard spatial voting model, the explanation herein recognizes that extremists are distinguished not only by their political positions, but also by the intensity with which they hold them. The paper uses an extension of Aumann and Kurz's (Econometrica 45(5):1137\textendash 1161, 1977) bargaining model to endogenize moderation and extremism in the context of democratic voting. The extension shows that low-income voters tend to be bolder in their redistributive demands and high-income voters tend to be more tenacious in defending them. These hypotheses are evaluated empirically using the Political Action Panel Study.{$<$}/p{$>$}},
  journal = {Public Choice}
}

@article{grafsteinProblemPolarizationa,
  title = {The Problem of Polarization},
  author = {Grafstein, Robert},
  doi = {10.1007/s11127-018-0547-z},
  abstract = {{$<$}h3 class="a-plus-plus"{$>$}Abstract{$<$}/h3{$>$}                     {$<$}p class="a-plus-plus"{$>$}This paper offers a unified political economy explanation of political extremism and moderation regarding income redistribution. Unlike the standard spatial voting model, the explanation herein recognizes that extremists are distinguished not only by their political positions, but also by the intensity with which they hold them. The paper uses an extension of Aumann and Kurz's (Econometrica 45(5):1137\textendash 1161, 1977) bargaining model to endogenize moderation and extremism in the context of democratic voting. The extension shows that low-income voters tend to be bolder in their redistributive demands and high-income voters tend to be more tenacious in defending them. These hypotheses are evaluated empirically using the Political Action Panel Study.{$<$}/p{$>$}},
  journal = {Public Choice}
}

@article{granovetter1973strength,
  title = {The {{Strength}} of {{Weak Ties}}},
  author = {Granovetter, Mark},
  year = {1973},
  volume = {78},
  pages = {1360--13},
  journal = {American Journal of Sociology},
  number = {6}
}

@incollection{granovetterStrengthWeakTies1977,
  title = {The {{Strength}} of {{Weak Ties}}},
  booktitle = {Social {{Networks}}},
  author = {Granovetter, Mark S.},
  year = {1977},
  pages = {347--367},
  publisher = {{Elsevier}},
  doi = {10.1016/B978-0-12-442450-0.50025-0},
  isbn = {978-0-12-442450-0},
  language = {en}
}

@inproceedings{granthamCreatingPerceptualUncertainty2020,
  title = {Creating Perceptual Uncertainty in Agent-Based Models with Social Interactions},
  booktitle = {Proceedings of the 2020 {{Spring Simulation Conference}}},
  author = {Grantham, Ethan O. and Giabbanelli, Philippe J.},
  year = {2020},
  month = may,
  pages = {1--12},
  publisher = {{Society for Computer Simulation International}},
  address = {{Fairfax, Virginia}},
  abstract = {Simple Agent-Based Models (ABMs) of social influence assume that agents can perfectly discriminate between the actions of their peers or implicitly agree on a population-wide definition of states such as 'healthy' or 'unhealthy'. In reality, mistakes are a part of being human and incorrectly estimating the state of a peer is no exception. For instance, experimental studies show that whether we find a food 'healthy' also depends on the body size of those who eat it. In this paper, we introduce norm perception errors in models from common application areas of ABMs, namely computational sociology and public health. Using simulations, we examined whether an increase in perceptual uncertainty changed the outcome of the models reported by their authors. We found that the effect depends on the model: even frequent incorrect judgments by the agents had no effect in an eating model whereas correlations were statistically significant in a segregation model.},
  file = {/home/aleksandar/Dropbox/Zotero/Grantham_Giabbanelli/Grantham_Giabbanelli_2020_Creating perceptual uncertainty in agent-based models with social interactions.pdf},
  isbn = {978-1-71381-288-3},
  series = {{{SpringSim}} '20}
}

@inproceedings{grayTrustPropagationSmall2003,
  title = {Trust {{Propagation}} in {{Small Worlds}}},
  booktitle = {Trust {{Management}}},
  author = {Gray, Elizabeth and Seigneur, Jean-Marc and Chen, Yong and Jensen, Christian},
  editor = {Nixon, Paddy and Terzis, Sotirios},
  year = {2003},
  pages = {239--254},
  publisher = {{Springer}},
  address = {{Berlin, Heidelberg}},
  doi = {10.1007/3-540-44875-6_17},
  abstract = {The possibility of a massive, networked infrastructure of diverse entities partaking in collaborative applications with each other increases more and more with the proliferation of mobile devices and the development of ad hoc networking technologies. In this context, traditional security measures do not scale well. We aim to develop trust-based security mechanisms using small world concepts to optimise formation and propagation of trust amongst entities in these vast networks. In this regard, we surmise that in a very large mobile ad hoc network, trust, risk, and recommendations can be propagated through relatively short paths connecting entities. Our work describes the design of trust-formation and risk-assessment systems, as well as that of an entity recognition scheme, within the context of the small world network topology.},
  file = {/home/aleksandar/Documents/Zotero/Gray et al/Gray et al_2003_Trust Propagation in Small Worlds.pdf},
  isbn = {978-3-540-44875-4},
  language = {en},
  series = {Lecture {{Notes}} in {{Computer Science}}}
}

@article{greenCommentaryCoefficientAlpha2009,
  title = {Commentary on {{Coefficient Alpha}}: {{A Cautionary Tale}}},
  shorttitle = {Commentary on {{Coefficient Alpha}}},
  author = {Green, Samuel B. and Yang, Yanyun},
  year = {2009},
  month = mar,
  volume = {74},
  pages = {121--135},
  issn = {1860-0980},
  doi = {10.1007/s11336-008-9098-4},
  abstract = {The general use of coefficient alpha to assess reliability should be discouraged on a number of grounds. The assumptions underlying coefficient alpha are unlikely to hold in practice, and violation of these assumptions can result in nontrivial negative or positive bias. Structural equation modeling was discussed as an informative process both to assess the assumptions underlying coefficient alpha and to estimate reliability},
  journal = {Psychometrika},
  language = {en},
  number = {1}
}

@article{greveHistoryPresentInstitutional2014,
  title = {History and the Present: {{Institutional}} Legacies in Communities of Organizations},
  shorttitle = {History and the Present},
  author = {Greve, Henrich R. and Rao, Hayagreeva},
  year = {2014},
  volume = {34},
  pages = {27--41},
  issn = {01913085},
  doi = {10.1016/j.riob.2014.09.002},
  journal = {Research in Organizational Behavior},
  language = {en}
}

@techreport{griesMarketBeliefSystems2020,
  title = {The {{Market}} for {{Belief Systems}}: {{A Formal Model}} of {{Ideological Choice}}},
  shorttitle = {The {{Market}} for {{Belief Systems}}},
  author = {Gries, Thomas and Mueller, Veronika and Jost, John},
  year = {2020},
  month = sep,
  institution = {{Politics and International Relations}},
  doi = {10.33774/apsa-2020-ndk81},
  abstract = {Belief systems play a crucial role when it comes to guiding human information processing, evaluation, judgement, behavior, and social coordination. But why do individuals and groups adopt the specific ideologies they do? And is it possible to use the tools of economics to understand the decisions that are made in the market for ideology? To address these and related questions, we synthesize insights garnered from standard rational choice models, characteristics demand theory, and the distance theory of voting, as well as theory and research on ``elective affinities'' in psychology. We offer a formal analysis of the role of psychological and consumption needs in shaping the individual's choice of ideology under circumstances of uncertainty and limited resources and other constraints, including informational costs associated with learning about the potential match values of specific ideologies. After providing a few examples, we mention one non-obvious implication of our model, namely that people can be ``wrong'' about their own ideological preferences according to the criteria of rational consistency and utility maximization.},
  file = {/home/aleksandar/Zotero/storage/3BHCUIQR/Gries et al. - 2020 - The Market for Belief Systems A Formal Model of I.pdf},
  language = {en},
  type = {Preprint}
}

@article{grigoropoulosAttitudesSameSexMarriage2019,
  title = {Attitudes {{Toward Same}}-{{Sex Marriage}} in a {{Greek Sample}}},
  author = {Grigoropoulos, Iraklis N.},
  year = {2019},
  month = jun,
  volume = {23},
  pages = {415--424},
  issn = {1095-5143, 1936-4822},
  doi = {10.1007/s12119-018-9565-8},
  journal = {Sexuality \& Culture},
  language = {en},
  number = {2}
}

@article{grimmettInfluenceCompromiseTwotier,
  title = {On Influence and Compromise in Two-Tier Voting Systems},
  author = {Grimmett, Geoffrey R.},
  doi = {10.1016/j.mathsocsci.2019.05.003},
  abstract = {{$<$}p{$>$}We examine two aspects of the mathematical basis for two-tier voting systems, such as that of the Council of the European Union. These aspects concern the use of square-root weights and the choice of quota.{$<$}/p{$><$}p{$>$}Square-root weights originate in the Penrose square-root system, which assumes that votes are cast independently and uniformly at random, and is based around the concept of equality of influence of the voters across the Union. There are (at least) two distinct definitions of influence in current use in probability theory, namely, {$<$}em{$>$}absolute{$<$}/em{$>$} and {$<$}em{$>$}conditional influence{$<$}/em{$>$}. These are in agreement when the underlying random variables are independent, but not generally. We review their possible implications for two-tier voting systems, especially in the context of the so-called collective bias model. We show that the two square-root laws invoked by Penrose are unified through the use of conditional influence.{$<$}/p{$><$}p{$>$}In an elaboration of the square-root system, S\l omczy\'nski and \.Zyczkowskihave proposed an exact value for the quota {$<$}math{$>$}q=q{${_\ast}<$}/math{$>$} to be achieved in a successful vote of a two-tier system, and they have presented numerical and theoretical evidence in its support. We indicate some numerical and mathematical issues arising in the use of a Gaussian (or normal) approximation in this context, and we propose that other values of {$<$}math{$>$}q{$<$}/math{$>$} may be as good if not better than {$<$}math{$>$}q{${_\ast}<$}/math{$>$}. We discuss certain aspects of the relationship between theoreticians and politicians in the design of a two-tier voting system, and we reach the conclusion that the choice of quota in the square-root system is an issue for politicians informed by theory.{$<$}/p{$>$}},
  journal = {Mathematical Social Science}
}

@article{grimmettInfluenceCompromiseTwotiera,
  title = {On Influence and Compromise in Two-Tier Voting Systems},
  author = {Grimmett, Geoffrey R.},
  doi = {10.1016/j.mathsocsci.2019.05.003},
  abstract = {{$<$}p{$>$}We examine two aspects of the mathematical basis for two-tier voting systems, such as that of the Council of the European Union. These aspects concern the use of square-root weights and the choice of quota.{$<$}/p{$><$}p{$>$}Square-root weights originate in the Penrose square-root system, which assumes that votes are cast independently and uniformly at random, and is based around the concept of equality of influence of the voters across the Union. There are (at least) two distinct definitions of influence in current use in probability theory, namely, {$<$}em{$>$}absolute{$<$}/em{$>$} and {$<$}em{$>$}conditional influence{$<$}/em{$>$}. These are in agreement when the underlying random variables are independent, but not generally. We review their possible implications for two-tier voting systems, especially in the context of the so-called collective bias model. We show that the two square-root laws invoked by Penrose are unified through the use of conditional influence.{$<$}/p{$><$}p{$>$}In an elaboration of the square-root system, S\l omczy\'nski and \.Zyczkowskihave proposed an exact value for the quota {$<$}math{$>$}q=q{${_\ast}<$}/math{$>$} to be achieved in a successful vote of a two-tier system, and they have presented numerical and theoretical evidence in its support. We indicate some numerical and mathematical issues arising in the use of a Gaussian (or normal) approximation in this context, and we propose that other values of {$<$}math{$>$}q{$<$}/math{$>$} may be as good if not better than {$<$}math{$>$}q{${_\ast}<$}/math{$>$}. We discuss certain aspects of the relationship between theoreticians and politicians in the design of a two-tier voting system, and we reach the conclusion that the choice of quota in the square-root system is an issue for politicians informed by theory.{$<$}/p{$>$}},
  journal = {Mathematical Social Science}
}

@book{grimmettRandomclusterModel2006,
  title = {The Random-Cluster Model},
  author = {Grimmett, Geoffrey},
  year = {2006},
  publisher = {{Springer}},
  address = {{Dordrecht; New York}},
  abstract = {"The random-cluster model has emerged in recent years as a key tool in the mathematical study of ferromagnetism. It may be viewed as an extension of percolation to include Ising and Potts models, and its analysis is a mix of arguments from probability and geometry. This systematic study includes accounts of the subcritical and supercritical phases, together with clear statements of important open problems. There is an extensive treatment of the first-order (discontinuous) phase transition, as well as a chapter devoted to applications of the random-cluster method to other models of statistical physics."--Jacket.},
  annotation = {OCLC: 70177985},
  isbn = {978-3-540-32890-2 978-3-642-06943-7},
  language = {English}
}

@techreport{gronauBayesianInferenceMultidimensional2020,
  title = {Bayesian {{Inference}} for {{Multidimensional Scaling Representations}} with {{Psychologically}}-{{Interpretable Metrics}}},
  author = {Gronau, Quentin Frederik and Lee, Michael David},
  year = {2020},
  month = jan,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/5zmep},
  abstract = {Multidimensional scaling (MDS) models represent stimuli as points in a space consisting of a number of psychological dimensions, such that the distance between pairs of points corresponds to the dissimilarity between the stimuli. Two fundamental challenges in inferring MDS representations from data involve inferring the appropriate number of dimensions, and the metric structure of the space used to measure distance. We approach both challenges as Bayesian model-selection problems. Treating MDS as a generative model, we define priors needed for model identifiability under metrics corresponding to psychologically separable and psychologically integral stimulus domains. We then apply a differential evolution Markovchain Monte Carlo (DE-MCMC) method for parameter inference, and a Warp-III method for model selection. We apply these methods to five previous data sets, which collectively test the ability of the methods to infer an appropriate dimensionality and to infer whether stimuli are psychologically separable or integral. We demonstrate that our methods produce sensible results, but note a number of remaining technical challenges that need to be solved before the method can easily and generally be applied. We also note the theoretical promise of the generative modeling perspective, discussing new and extended models of MDS representation that could be developed.},
  language = {en},
  type = {Preprint}
}

@techreport{gronauPrimerBayesianModelAveraged2020,
  title = {A {{Primer}} on {{Bayesian Model}}-{{Averaged Meta}}-{{Analysis}}},
  author = {Gronau, Quentin Frederik and Heck, Daniel W. and Berkhout, Sophie and Haaf, Julia M. and Wagenmakers, Eric-Jan},
  year = {2020},
  month = apr,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/97qup},
  abstract = {Meta-analysis is the predominant approach for quantitatively synthesizing a set of studies. If the studies themselves are of high quality, meta-analysis can provide valuable insights into the current scientific state of knowledge about a particular phenomenon. In psychological science, the most common approach is to conduct frequentist metaanalysis. In this primer, we discuss an alternative method, Bayesian model-averaged meta-analysis. This procedure combines the results of four Bayesian meta-analysis models: (1) fixed-effect null hypothesis, (2) fixed-effect alternative hypothesis, (3) random-effects null hypothesis, and (4) random-effects alternative hypothesis. These models are combined according to their plausibilities in light of the observed data to address the two key questions ``Is the overall effect non-zero?'' and ``Is there between-study variability in effect size?''. Bayesian modelaveraged meta-analysis therefore avoids the need to select either a fixedeffect or random-effects model and instead takes into account model uncertainty in a principled manner.},
  language = {en},
  type = {Preprint}
}

@article{grosSelfInducedClass2020,
  title = {Self Induced Class Stratification in Competitive Societies of Agents: {{Nash}} Stability in the Presence of Envy},
  shorttitle = {Self Induced Class Stratification in Competitive Societies of Agents},
  author = {Gros, Claudius},
  year = {2020},
  month = may,
  abstract = {Envy, the inclination to compare rewards, can be expected to unfold when inequalities in terms of payoff differences are generated in competitive societies. It is shown that increasing levels of envy lead inevitably to a self-induced separation into a lower and an upper class. Class stratification is Nash stable and strict, with members of the same class receiving identical rewards. Upper class agents play exclusively pure strategies, all lower class agents the same mixed strategy. The fraction of upper class agents decreases progressively with larger levels of envy, until a single upper class agent is left. Numerical simulations and a complete analytic treatment of a basic reference model, the shopping trouble model, are presented. The properties of the class-stratified society are universal and only indirectly controllable through the underlying utility function, which implies that class stratified societies are intrinsically resistant to political control. Implications for human societies are discussed. It is pointed out that the repercussions of envy are amplified when societies become increasingly competitive.},
  archivePrefix = {arXiv},
  eprint = {2005.11966},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Gros/Gros_2020_Self induced class stratification in competitive societies of agents.pdf},
  journal = {arXiv:2005.11966 [nlin, physics:physics]},
  primaryClass = {nlin, physics:physics}
}

@techreport{groszTabooExplicitCausal2020,
  title = {The {{Taboo Against Explicit Causal Inference}} in {{Nonexperimental Psychology}}},
  author = {Grosz, Michael P. and Rohrer, Julia Marie and Thoemmes, Felix},
  year = {2020},
  month = mar,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/8hr7n},
  abstract = {Causal inference is a central goal of research. However, most psychologists refrain from explicitly addressing causal research questions and avoid drawing causal inference on the basis of nonexperimental evidence. We argue that this taboo against causal inference in nonexperimental psychology impairs study design and data analysis, holds back cumulative research, leads to a disconnect between original findings and how they are interpreted in subsequent work, and limits the relevance of nonexperimental psychology for policy making. At the same time, the taboo does not prevent researchers from interpreting findings as causal effects\textemdash the inference is simply made implicitly, and assumptions remain unarticulated. Thus, we recommend that nonexperimental psychologists begin to talk openly about causal assumptions and causal effects. Only then can researchers take advantage of recent methodological advances in causal reasoning and analysis and develop a solid understanding of the underlying causal mechanisms that can inform future research, theory, and policy makers.},
  file = {/home/aleksandar/Dropbox/Zotero/Grosz et al/Grosz et al_2020_The Taboo Against Explicit Causal Inference in Nonexperimental Psychology.pdf},
  language = {en},
  type = {Preprint}
}

@article{guesmiMultidimensionalCommunityDiscovering,
  title = {Multidimensional Community Discovering in Heterogeneous Social Networks},
  author = {Guesmi, Soumaya and Trabelsi, Chiraz and Latiri, Chiraz},
  volume = {n/a},
  pages = {e5809},
  issn = {1532-0634},
  doi = {10.1002/cpe.5809},
  abstract = {Multidimensional community discovering in heterogeneous social networks is an important issue. Many approaches have been proposed for community discovering in heterogeneous networks. However, they have focused only on topological properties of these networks, ignoring the embedded semantic information. As the solution to this information glut limit, we propose, in this article, a new multidimensional community discovering approach, which incorporates the multiple types of objects and relationships, derived from a heterogeneous networks. First, we propose to construct the concept lattice family CLF to represent the different objects and relations of the heterogeneous social networks based on the relational concept analysis techniques. Then after we introduce a new algorithm that explores such CLF and extract the multidimensional communities. Carried out experiments on real datasets enhance the effectiveness of our proposal and open promising issues.},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5809},
  copyright = {\textcopyright{} 2020 John Wiley \& Sons, Ltd.},
  file = {/home/aleksandar/Zotero/storage/RDSAKFQT/cpe.html},
  journal = {Concurrency and Computation: Practice and Experience},
  language = {en},
  number = {n/a}
}

@inproceedings{guhaPropagationTrustDistrust2004,
  title = {Propagation of Trust and Distrust},
  booktitle = {{{WWW}} '04},
  author = {Guha, R. and Kumar, Ravi and Raghavan, P. and Tomkins, A.},
  year = {2004},
  doi = {10.1145/988672.988727},
  abstract = {A (directed) network of people connected by ratings or trust scores, and a model for propagating those trust scores, is a fundamental building block in many of today's most successful e-commerce and recommendation systems. We develop a framework of trust propagation schemes, each of which may be appropriate in certain circumstances, and evaluate the schemes on a large trust network consisting of 800K trust scores expressed among 130K people. We show that a small number of expressed trusts/distrust per individual allows us to predict trust between any two people in the system with high accuracy. Our work appears to be the first to incorporate distrust in a computational trust propagation setting.}
}

@article{guimeraOneModelRule2020,
  title = {One Model to Rule Them All in Network Science?},
  author = {Guimer{\`a}, Roger},
  year = {2020},
  month = oct,
  volume = {117},
  pages = {25195--25197},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.2017807117},
  journal = {Proceedings of the National Academy of Sciences},
  language = {en},
  number = {41}
}

@article{guiThreeFacesOnline2020,
  title = {Three Faces of the Online Leftists: {{An}} Exploratory Study Based on Case Observations and Big-Data Analysis},
  shorttitle = {Three Faces of the Online Leftists},
  author = {Gui, Yong and Huang, Ronggui and Ding, Yi},
  year = {2020},
  month = jan,
  volume = {6},
  pages = {67--101},
  issn = {2057-150X, 2057-1518},
  doi = {10.1177/2057150X19896537},
  abstract = {Left-leaning social thoughts are not a unitary and coherent theoretical system, and leftists can be divided into divergent groups. Based on inductive qualitative observations, this article proposes a theoretical typology of two dimensions of theoretical resources and position orientations to describe left-wing social thoughts communicated in online space. Empirically, we used a mixed approach, an integration of case observations and big-data analyses of Weibo tweets, to investigate three types of left-leaning social thoughts. The identified left-leaning social thoughts include state-centered leftism, populist leftism, and liberal leftism, which are consistent with the proposed theoretical typology. State-centered leftism features strong support of the state and the current regime and a negative attitude toward the West, populist leftism is characterized by unequivocal affirmation of the revolutionary legacy and support for disadvantaged grassroots, and liberal leftism harbors a grassroots position and a decided affirmation of individual rights. In addition, we used supervised machine learning and social network analysis techniques to identify online communities that harbor the afore-mentioned left-leaning social thoughts and analyzed the interaction patterns within and across communities as well as the evolutions of community structures. We found that during the study period of 2012\textendash 2014, the liberal leftists gradually declined and the corresponding communities dissolved; the interactions between populist leftists and state-centered leftists intensified, and the ideational cleavage between these two camps increased the online confrontations. This article demonstrates that the mixed method approach of integrating traditional methods with big-data analytics has enormous potential in the sub-discipline of digital sociology.},
  journal = {Chinese Journal of Sociology},
  language = {en},
  number = {1}
}

@article{gundelachDecentralisationPoliticalInequality2019,
  title = {Decentralisation and Political Inequality: A Comparative Analysis of Unequal Turnout in {{European}} Regions},
  shorttitle = {Decentralisation and Political Inequality},
  author = {Gundelach, Birte and Fatke, Matthias},
  year = {2019},
  month = sep,
  issn = {1740-388X},
  doi = {10.1057/s41295-019-00197-y},
  abstract = {This article analyses whether and how the persistent positive relationship between socioeconomic status and political participation can be moderated by institutional design. Hopes to boost turnout rates of socially disadvantaged citizens often rest upon the introduction of participatory institutions. Jean-Jacques Rousseau, Alexis de Tocqueville and John Stuart Mill had already asserted claims about the educative effect of close political institutions at the local level, which presumably result in a decrease in social inequality. More recently, campaigns for greater regional authority throughout Europe have represented a demand for opportunities to participate in decentralised, accessible polities. Based on data from 259 regions in Europe, we investigate whether political decentralisation and increased opportunities to participate are appropriate means of mitigating political inequality. The results not only fail to meet expectations but show that decentralisation in fact reinforces unequal voter turnout. These findings are particularly relevant for combatting inequality and indicating the potential side effects of decentralisation campaigns.},
  journal = {Comparative European Politics},
  language = {en}
}

@article{guntherPartiesElectoralBehavior2005,
  title = {Parties and Electoral Behavior in {{Southern Europe}}},
  author = {Gunther, Richard},
  year = {2005},
  month = apr,
  volume = {37},
  pages = {253},
  issn = {00104159},
  doi = {10.2307/20072889},
  journal = {Comparative Politics},
  language = {en},
  number = {3}
}

@article{guptaRecentTrendsCommunity2020,
  title = {Recent Trends on Community Detection Algorithms: {{A}} Survey},
  shorttitle = {Recent Trends on Community Detection Algorithms},
  author = {Gupta, Sumit and Singh, Dhirendra Pratap},
  year = {2020},
  month = sep,
  pages = {2050408},
  publisher = {{World Scientific Publishing Co.}},
  issn = {0217-9849},
  doi = {10.1142/S0217984920504084},
  abstract = {In today's world scenario, many of the real-life problems and application data can be represented with the help of the graphs. Nowadays technology grows day by day at a very fast rate; applications generate a vast amount of valuable data, due to which the size of their representation graphs is increased. How to get meaningful information from these data become a hot research topic. Methodical algorithms are required to extract useful information from these raw data. These unstructured graphs are not scattered in nature, but these show some relationships between their basic entities. Identifying communities based on these relationships improves the understanding of the applications represented by graphs. Community detection algorithms are one of the solutions which divide the graph into small size clusters where nodes are densely connected within the cluster and sparsely connected across. During the last decade, there are lots of algorithms proposed which can be categorized into mainly two broad categories; non-overlapping and overlapping community detection algorithm. The goal of this paper is to offer a comparative analysis of the various community detection algorithms. We bring together all the state of art community detection algorithms related to these two classes into a single article with their accessible benchmark data sets. Finally, we represent a comparison of these algorithms concerning two parameters: one is time efficiency, and the other is how accurately the communities are detected.},
  file = {/home/aleksandar/Zotero/storage/6J9VW8CP/S0217984920504084.html},
  journal = {Modern Physics Letters B}
}

@article{guthPartyChoiceEurope,
  title = {Party Choice in {{Europe}}: {{Social}} Cleavages and the Rise of Populist Parties},
  author = {Guth, James L and Nelsen, Brent F},
  doi = {10.1177/1354068819853965},
  abstract = {Does the rise of populist parties of the right and left indicate the fading of the traditional left\textendash right cleavage and the rise of a new transnational cleavage? Our analysis finds evidence of a continued left\textendash right cleavage that divides European parties by religion and class. Our analysis also finds strong evidence for an additional transnational cleavage that pits the populists of right and left against the traditional parties of the "frozen" center. Right-Wing Populist parties attract young, working-class, and less educated voters, more often male, who are disconnected from religious institutions, perceive the national economy and their own economic status in a negative vein, and do not like immigrants. They distrust their own national government and the European Union. The Populist Left trends even younger, lower in status and education, more pessimistic about economic concerns, and just as hostile to political elites. The populists\textemdash left and right\textemdash may be divided over some aspects of modern culture, but they are united in their opposition to European elites.},
  file = {/home/aleksandar/Documents/Zotero/Guth_Nelsen/Guth_Nelsen_Party choice in Europe.pdf},
  journal = {Party Politics}
}

@article{guthPartyChoiceEuropea,
  title = {Party Choice in {{Europe}}: {{Social}} Cleavages and the Rise of Populist Parties},
  author = {Guth, James L and Nelsen, Brent F},
  doi = {10.1177/1354068819853965},
  abstract = {Does the rise of populist parties of the right and left indicate the fading of the traditional left\textendash right cleavage and the rise of a new transnational cleavage? Our analysis finds evidence of a continued left\textendash right cleavage that divides European parties by religion and class. Our analysis also finds strong evidence for an additional transnational cleavage that pits the populists of right and left against the traditional parties of the "frozen" center. Right-Wing Populist parties attract young, working-class, and less educated voters, more often male, who are disconnected from religious institutions, perceive the national economy and their own economic status in a negative vein, and do not like immigrants. They distrust their own national government and the European Union. The Populist Left trends even younger, lower in status and education, more pessimistic about economic concerns, and just as hostile to political elites. The populists\textemdash left and right\textemdash may be divided over some aspects of modern culture, but they are united in their opposition to European elites.},
  journal = {Party Politics}
}

@article{gyftopoulosTwitterbasedApproachNews,
  title = {A {{Twitter}}-Based Approach of News Media Impartiality in Multipartite Political Scenes},
  author = {Gyftopoulos, Sotirios and Drosatos, George and Stamatelatos, Giorgos and Efraimidis, Pavlos S.},
  doi = {10.1007/s13278-020-00642-x},
  abstract = {News dissemination in the modern world deploys online social networks (OSNs) to instantly and freely convey facts and opinions to Internet users worldwide. Recent research studies the structure of the graph formed by the relationships between news readers and media outlets in OSNs to investigate the profile of the media and derive their political leanings. In this work, we focus on the notion of political impartiality in multipartite political scenes. Our aim is to describe the graph-theoretic attributes of the ideal outlet that exhibits an impartial stance towards all political groups and propose a methodology based on Twitter, an OSN with profound informative and political profile, to algorithmically approximate this ideal medium and evaluate the deviation of popular outlets from it. The magnitude of deviation is used to rank the existing outlets based on their political impartiality and, hence, tackle the bewildering question: \emph{Which are the most impartial news media in a political scene?}. We utilize our techniques on a snapshot of the Twitter subgraph concerning the Greek political and news media scene in April 2018. The results of our approach are juxtaposed with the findings of a survey provided to a group of political scientists and the efficiency of our proposed methodology is soundly confirmed.},
  journal = {Social Network Analysis and Mining}
}

@article{haackLegitimacyRevisitedDisentangling2020,
  title = {Legitimacy {{Revisited}}: {{Disentangling Propriety}}, {{Validity}}, and {{Consensus}}},
  shorttitle = {Legitimacy {{Revisited}}},
  author = {Haack, Patrick and Schilke, Oliver and Zucker, Lynne},
  year = {2020},
  month = jul,
  pages = {joms.12615},
  issn = {0022-2380, 1467-6486},
  doi = {10.1111/joms.12615},
  abstract = {Recent research has conceptualized legitimacy as a multi-level phenomenon comprising propriety and validity. Propriety refers to an individual evaluator's belief that a legitimacy object is appropriate for its social context, whereas validity denotes an institutionalized, collective-level perception of appropriateness. In this article, we refine this multi-level understanding of legitimacy by adding a third, meso-level construct of ``consensus'', which we define as the agreement between evaluators' propriety beliefs. Importantly, validity and consensus are distinct and can be incongruent, given that an institutionalized perception can hide underlying disagreement. Disentangling validity from consensus is a crucial extension of the multi-level theory of legitimacy, because it enables an improved understanding of the legitimacy processes that precede sudden and unanticipated institutional change. In particular, while previous works considered revised propriety beliefs as the starting point for institutional change, our account emphasizes that the disclosure of the actual (vs. merely assumed) belief distribution within a social context may instigate institutional change. To study the interplay of propriety, validity, and consensus empirically, we propose a set of experimental designs specifically geared towards improving knowledge of the role of legitimacy and its components in institutional change.},
  file = {/home/aleksandar/Zotero/storage/BEL4MGFC/Haack et al. - 2020 - Legitimacy Revisited Disentangling Propriety, Val.pdf},
  journal = {Journal of Management Studies},
  language = {en}
}

@article{haberDAGOmittedObjects2020,
  title = {{{DAG With Omitted Objects Displayed}} ({{DAGWOOD}}): {{A}} Framework for Revealing Causal Assumptions in {{DAGs}}},
  shorttitle = {{{DAG With Omitted Objects Displayed}} ({{DAGWOOD}})},
  author = {Haber, Noah A. and Wood, Mollie E. and Wieten, Sarah and Breskin, Alexander},
  year = {2020},
  month = apr,
  abstract = {Directed acyclic graphs (DAGs) are frequently used in epidemiology as a guide to assess causal inference assumptions. However, DAGs show the model as assumed, but not the assumption decisions themselves. We propose a framework which reveals these hidden assumptions, both conceptually and graphically. The DAGWOOD framework combines a root DAG (representing the DAG in the proposed analysis), a set of branch DAGs (representing alternative hidden assumptions to the root DAG), a graphical overlay (represents the branch DAGs over the root DAG), and a ruleset governing them. All branch DAGs follow the same rules for validity: they must 1) change the root DAG, 2) be a valid, identifiable causal DAG, and either 3a) require a change in the adjustment set to estimate the effect of interest, or 3b) change the number of frontdoor paths. The set of branch DAGs corresponds to a list of alternative assumptions, where all members of the assumption list must be justifiable as being negligible or non-existent. A graphical overlay helps show these alternative assumptions on top of the root DAG. We define two types of branch DAGs: exclusion restrictions and misdirection restrictions. Exclusion restrictions add a single- or bi-directional arc between two existing nodes in the root DAG (e.g. direct pathways and colliders), while misdirection restrictions represent alternative pathways that could be drawn between objects (e.g., reversing the direction of causation for a controlled confounder turning that variable into a collider). Together, these represent all single-change assumptions to the root DAG. The DAGWOOD framework 1) makes explicit and organizes important causal model assumptions, 2) reinforces best DAG practices, 3) provides a framework for critical evaluation of causal models, and 4) can be used in iterative processes for generating causal models.},
  archivePrefix = {arXiv},
  eprint = {2004.04251},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/7RF5D76W/2004.html},
  journal = {arXiv:2004.04251 [stat]},
  primaryClass = {stat}
}

@article{hafnerDilemasManagingExpanding1999,
  title = {Dilemas in Managing the Expanding {{EU}}: {{The EU}} and Applicant States' Points of View},
  shorttitle = {Dilemas in Managing the Expanding {{EU}}},
  author = {Hafner, Danica Fink},
  year = {1999},
  month = jan,
  volume = {6},
  pages = {783--801},
  issn = {1350-1763, 1466-4429},
  doi = {10.1080/135017699343388},
  journal = {Journal of European Public Policy},
  language = {en},
  number = {5}
}

@book{hagenaarsAppliedLatentClass2002,
  title = {Applied Latent Class Analysis},
  author = {Hagenaars, Jacques A and McCutcheon, Allan L},
  year = {2002},
  publisher = {{Cambridge University Press}},
  address = {{Cambridge; New York}},
  abstract = {Applied Latent Class Analysis introduces several recent innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis have contributed essays to this volume, each presenting a key innovation to the basic LCM.},
  annotation = {OCLC: 70753838},
  isbn = {978-0-511-06594-1 978-0-511-06807-2 978-0-511-05963-6 978-0-511-49953-1 978-1-280-41726-9},
  language = {English}
}

@article{haidtIndividualDifferencesSensitivity1994,
  title = {Individual Differences in Sensitivity to Disgust: {{A}} Scale Sampling Seven Domains of Disgust Elicitors},
  shorttitle = {Individual Differences in Sensitivity to Disgust},
  author = {Haidt, Jonathan and McCauley, Clark and Rozin, Paul},
  year = {1994},
  month = may,
  volume = {16},
  pages = {701--713},
  issn = {0191-8869},
  doi = {10.1016/0191-8869(94)90212-7},
  abstract = {We describe the development of a reliable measure of individual differences in disgust sensitivity. The 32-item Disgust Scale includes 2 true-false and 2 disgust-rating items for each of 7 domains of disgust elicitors (food, animals, body products, sex, body envelope violations, death, and hygiene) and for a domain of magical thinking (via similarity and contagion) that cuts across the 7 domains of elicitors. Correlations with other scales provide initial evidence of convergent and discriminant validity: the Disgust Scale correlates moderately with Sensation Seeking (r= - 0.46) and with Fear of Death (r= 0.39), correlates weakly with Neuroticism (r = 0.23) and Psychoticism (r= - 0.25), and correlates negligibly with Self-Monitoring and the Eysenck Personality Questionnaire Extraversion and Lie scales. Females score higher than males on the Disgust Scale. We suggest that the 7 domains of disgust elicitors all have in common that they remind us of our animality and, especially, of our mortality. Thus we see disgust as a defensive emotion that maintains and emphasizes the line between human and animal.},
  file = {/home/aleksandar/Zotero/storage/ECBQNC8M/0191886994902127.html},
  journal = {Personality and Individual Differences},
  language = {en},
  number = {5}
}

@inproceedings{halbachInvestigatingKeyFactors2020,
  ids = {halbachInvestigatingKeyFactors2020a},
  title = {Investigating {{Key Factors}} for {{Social Network Evolution}} and {{Opinion Dynamics}} in an {{Agent}}-{{Based Simulation}}},
  booktitle = {Digital {{Human Modeling}} and {{Applications}} in {{Health}}, {{Safety}}, {{Ergonomics}} and {{Risk Management}}. {{Human Communication}}, {{Organization}} and {{Work}}},
  author = {Halbach, Patrick and Burbach, Laura and Belavadi, Poornima and Nakayama, Johannes and Plettenberg, Nils and Ziefle, Martina and Calero Valdez, Andr{\'e}},
  editor = {Duffy, Vincent G.},
  year = {2020},
  pages = {20--39},
  publisher = {{Springer International Publishing}},
  address = {{Cham}},
  doi = {10.1007/978-3-030-49907-5_2},
  abstract = {In recent years social media platforms have experienced increasing attention of researchers due to their capabilities of providing information and spreading opinions of individuals, thus establishing a new environment for opinion formation on a societal level. To gain a better understanding of the occurring opinion dynamics, the interactions between the users and the content that has been shared in those environments has to be investigated. With our work, we want to shed light on the part played by the underlying network structure as information spread relies directly on it and every user of social media is affected by it. Therefore, we analyzed the role of network properties and dealing with friendships in such networks using an agent-based model. Our results reveal the capability of such models for investigating the influence of these factors on opinion dynamics and encourage further investigation in this field of research.},
  file = {/home/aleksandar/Dropbox/Zotero/Halbach et al/Halbach et al_2020_Investigating Key Factors for Social Network Evolution and Opinion Dynamics in.pdf;/home/aleksandar/Dropbox/Zotero/Halbach et al/Halbach et al_2020_Investigating Key Factors for Social Network Evolution and Opinion Dynamics in2.pdf},
  isbn = {978-3-030-49907-5},
  language = {en},
  series = {Lecture {{Notes}} in {{Computer Science}}}
}

@book{haleWhyNotParties2006,
  title = {Why Not Parties in {{Russia}}? {{Democracy}}, Federalism, and the State},
  shorttitle = {Why Not Parties in {{Russia}}?},
  author = {Hale, Henry E.},
  year = {2006},
  publisher = {{Cambridge University Press}},
  address = {{Cambridge}},
  isbn = {978-0-521-84409-3},
  lccn = {JN6695 .H35 2006}
}

@article{hallquistProblemsCentralityMeasures2019,
  ids = {hallquistProblemsCentralityMeasure,hallquistProblemsCentralityMeasuresa,hallquistProblemsCentralityMeasuresb},
  title = {Problems with {{Centrality Measures}} in {{Psychopathology Symptom Networks}}: {{Why Network Psychometrics Cannot Escape Psychometric Theory}}},
  shorttitle = {Problems with {{Centrality Measures}} in {{Psychopathology Symptom Networks}}},
  author = {Hallquist, Michael N. and Wright, Aidan G. C. and Molenaar, Peter C. M.},
  year = {2019},
  month = aug,
  volume = {0},
  pages = {1--25},
  issn = {0027-3171},
  doi = {10.1080/00273171.2019.1640103},
  abstract = {Understanding patterns of symptom co-occurrence is one of the most difficult challenges in psychopathology research. Do symptoms co-occur because of a latent factor, or might they directly and causally influence one another? Motivated by such questions, there has been a surge of interest in network analyses that emphasize the putatively direct role symptoms play in influencing each other. In this critical paper, we highlight conceptual and statistical problems with using centrality measures in cross-sectional networks. In particular, common network analyses assume that there are no unmodeled latent variables that confound symptom co-occurrence. The traditions of clinical taxonomy and test development in psychometric theory, however, greatly increase the possibility that latent variables exist in symptom data. In simulations that include latent variables, we demonstrate that closeness and betweenness are vulnerable to spurious covariance among symptoms that connect subgraphs (e.g., diagnoses). We further show that strength is redundant with factor loading in several cases. Finally, if a symptom reflects multiple latent causes, centrality metrics reflect a weighted combination, undermining their interpretability in empirical data. Our results suggest that it is essential for network psychometric approaches to examine the evidence for latent variables prior to analyzing or interpreting patterns at the symptom level. Failing to do so risks identifying spurious relationships or failing to detect causally important effects. Altogether, we argue that centrality measures do not provide solid ground for understanding the structure of psychopathology when latent confounding exists.},
  journal = {Multivariate Behavioral Research},
  number = {0},
  pmid = {31401872}
}

@article{hallquistProblemsCentralityMeasures2019a,
  title = {Problems with {{Centrality Measures}} in {{Psychopathology Symptom Networks}}: {{Why Network Psychometrics Cannot Escape Psychometric Theory}}},
  shorttitle = {Problems with {{Centrality Measures}} in {{Psychopathology Symptom Networks}}},
  author = {Hallquist, Michael N. and Wright, Aidan G. C. and Molenaar, Peter C. M.},
  year = {2019},
  month = aug,
  pages = {1--25},
  issn = {0027-3171, 1532-7906},
  doi = {10.1080/00273171.2019.1640103},
  file = {/home/aleksandar/Zotero/storage/KVXNPGNV/Hallquist et al_2019_Problems with Centrality Measures in Psychopathology Symptom Networks.pdf},
  journal = {Multivariate Behavioral Research},
  language = {en}
}

@article{hallStatisticalMechanicsTwitter2019,
  title = {The Statistical Mechanics of {{Twitter}} Communities},
  author = {Hall, Gavin and Bialek, William},
  year = {2019},
  month = sep,
  volume = {2019},
  pages = {093406},
  issn = {1742-5468},
  doi = {10.1088/1742-5468/ab3af0},
  abstract = {We build models for the distribution of social states in Twitter communities. States can be defined by the participation versus silence of individuals in conversations that surround key words, and we approximate the joint distribution of these binary variables using the maximum entropy principle, finding the least structured models that match the mean probability of individuals tweeting and their pairwise correlations. These models provide very accurate, quantitative descriptions of higher order structure in these social networks. The parameters of these models seem poised close to critical surfaces in the space of possible models, and we observe scaling behavior of the data under coarse-graining. These results suggest that simple models, grounded in statistical physics, may provide a useful point of view on the larger data sets now emerging from complex social systems.},
  journal = {Journal of Statistical Mechanics: Theory and Experiment},
  language = {en},
  number = {9}
}

@book{halmosNaiveSetTheory1974,
  title = {Naive {{Set Theory}}},
  author = {Halmos, Paul R.},
  editor = {Axler, S. and Gehring, F. W. and Ribet, K. A.},
  year = {1974},
  publisher = {{Springer New York}},
  address = {{New York, NY}},
  doi = {10.1007/978-1-4757-1645-0},
  isbn = {978-0-387-90104-6 978-1-4757-1645-0},
  language = {en},
  series = {Undergraduate {{Texts}} in {{Mathematics}}}
}

@article{handlinObservingIncumbentAbuses2017,
  title = {Observing Incumbent Abuses: Improving Measures of Electoral and Competitive Authoritarianism with New Data},
  shorttitle = {Observing Incumbent Abuses},
  author = {Handlin, Samuel},
  year = {2017},
  month = jan,
  volume = {24},
  pages = {41--60},
  issn = {1351-0347, 1743-890X},
  doi = {10.1080/13510347.2016.1149814},
  file = {/home/aleksandar/Dropbox/Zotero/Handlin/Handlin_2017_Observing incumbent abuses.pdf},
  journal = {Democratization},
  language = {en},
  number = {1}
}

@techreport{hanelConductingHighImpact2020,
  title = {Conducting {{High Impact Research With Limited Financial Resources}} ({{While Working From Home}})},
  author = {Hanel, Paul H. P.},
  year = {2020},
  month = may,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/s3fcu},
  abstract = {The Covid-19 pandemic has far-reaching implications for researchers.  For example, many researchers cannot access their labs anymore and are hit by budget-cuts from their institutions.  Luckily, there are a range of ways how high-quality research can be conducted without funding and face-to-face interactions.  In the present paper, I discuss eight such possibilities, including meta-analyses, secondary data analyses, web-scrapping, scientometrics, or sharing one's expert knowledge (e.g., writing tutorials).  Most of these possibilities can be done from home, as they require only access to a computer, the internet, and time; but no state-of-the art equipment or funding to pay for participants.  Thus, they are particularly relevant for researchers with limited financial resources beyond pandemics and quarantines.},
  language = {en},
  type = {Preprint}
}

@article{hansenWhatExpectWhen,
  ids = {hansenWhatExpectWhenb,hansenWhatExpectWhenc,hansenWhatExpectWhend},
  title = {What to Expect When You're Electing: The Relationship between Far-Right Strength and Citizenship Policy in {{Europe}}},
  author = {Hansen, Michael A. and Clemens, Jennifer L.},
  doi = {10.1057/s41295-018-0120-7},
  abstract = {The analysis builds on previous research exploring the impact of far-right support on citizenship policy. Using Bayesian analyses, this research evaluates the impact of far-right success on citizenship policy restrictiveness and citizenship policy outcomes per year across 29 European countries between 2003\textendash 2014. Results reveal that far-right success is a statistically and substantively significant factor in determining citizenship policy restrictiveness as well as rates of naturalization. However, differential levels of impact suggest that far-right influence is not uniform throughout the policy process.},
  journal = {Comparative European Politics}
}

@article{harbersDecentralizationDevelopmentNationalized2010,
  title = {Decentralization and the Development of Nationalized Party Systems in New Democracies: {{Evidence}} from {{Latin America}}},
  shorttitle = {Decentralization and the {{Development}} of {{Nationalized Party Systems}} in {{New Democracies}}},
  author = {Harbers, Imke},
  year = {2010},
  month = may,
  volume = {43},
  pages = {606--627},
  issn = {0010-4140, 1552-3829},
  doi = {10.1177/0010414008330285},
  journal = {Comparative Political Studies},
  language = {en},
  number = {5}
}

@article{hardyParadoxProductivityQuarantine2020,
  title = {The Paradox of Productivity during Quarantine: An Agent-Based Simulation},
  shorttitle = {The Paradox of Productivity during Quarantine},
  author = {Hardy, Peter and Marcolino, Leandro Soriano and Fontanari, Jos{\'e} F.},
  year = {2020},
  month = aug,
  abstract = {Economies across the globe were brought to their knees due to lockdowns and social restriction measures to contain the spread of the SARS-CoV-2, despite the quick switch to remote working. This downfall may be partially explained by the "water cooler effect", which holds that higher levels of social interaction lead to higher productivity due to a boost in people's mood. Somewhat paradoxically, however, there are reports of increased productivity in the remote working scenario. Here we address quantitatively this issue using an agent-based model to simulate a workplace with extrovert and introvert agent stereotypes that differ solely on their propensities to initiate a social interaction. We find that the effects of curtailing social interactions depend on the proportion of the stereotypes in the working group: while the social restriction measures always have a negative impact on the productivity of groups composed predominantly of introverts, they may actually improve the productivity of groups composed predominantly of extroverts, which offers then an explanation for the paradox of productivity during quarantine.},
  archivePrefix = {arXiv},
  eprint = {2008.09461},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/9C6B4QTW/Hardy et al. - 2020 - The paradox of productivity during quarantine an .pdf},
  journal = {arXiv:2008.09461 [physics]},
  language = {en},
  primaryClass = {physics}
}

@article{harper2001ParliamentaryPresidential2003,
  title = {The 2001 Parliamentary and Presidential Elections in {{Bulgaria}}},
  author = {Harper, M.A.G.},
  year = {2003},
  month = jun,
  volume = {22},
  pages = {335--344},
  issn = {02613794},
  doi = {10.1016/S0261-3794(02)00051-3},
  journal = {Electoral Studies},
  language = {en},
  number = {2}
}

@techreport{harperIdeologicalMeasurementSocial2020,
  title = {Ideological Measurement in Social and Personality Psychological Science},
  author = {Harper, Craig A.},
  year = {2020},
  month = mar,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/wpsje},
  abstract = {As the domains of social and personality psychological science undergo marked changes in their approach to research (e.g., open science practices, and addressing the replication crisis), it is important to undertake a full review of the tools and measures that we have at our disposal. In addition, the growing sense of political and ideological polarization in contemporary western democracies necessitates a coherent and internally consistent approach to studying politically and ideologically sensitive topics. This paper explores the measurement and study of such topics and posits that claims about symmetries and asymmetries between political and ideological partisans may be rooted in different measurement approaches. A more consistent and ecologically valid approach to studying partisan engagement with political topics, and for a move away from examining (a)symmetries via self-report individual difference measures that are devoid of contextual information is advocated.},
  file = {/home/aleksandar/Dropbox/Zotero/Harper/Harper_2020_Ideological measurement in social and personality psychological science.pdf},
  language = {en},
  type = {Preprint}
}

@article{harrisonDemocraticFrustrationConcept2020,
  title = {Democratic {{Frustration}}: {{Concept}}, {{Dimensions}} and {{Behavioural Consequences}}},
  shorttitle = {Democratic {{Frustration}}},
  author = {{Harrison}},
  year = {2020},
  month = feb,
  volume = {10},
  pages = {19},
  issn = {2075-4698},
  doi = {10.3390/soc10010019},
  abstract = {Using insights from the psychology literature, this article introduces and operationalises the concept of `democratic frustration' to shed new light on the pathologies of democratic crises. While political scientists have devoted ample attention to democratic crises and dissatisfaction, this article suggests that citizens' frequent references to their ``frustration'' should be taken more literally. Specifically, it suggests that citizens become frustrated when a perceived democratic delivery deficit interacts with a strong democratic expectation or desire. The article tests this model using two original surveys run in the UK during the 2017 General Election and 2019 European Parliament elections. By measuring expectations and delivery deficit separately, the article maps democratic frustration vis-\`a-vis alternative concepts such as apathy, criticality, and cynicism, and shows that it is more widespread as an expectation\textendash deficit combination than any of them. It suggests that democratic frustration comprises of three dimensions: ideological, institutional and political. Adapting insights from the psychology of frustration that show it usually results in expressions of withdrawal, anger, or aggression, the article then explores how the three dimensions of frustration typically result in different pathologies. Ideological frustration leads to abstention (withdrawal), institutional frustration to peaceful demonstrations or radical vote (anger) and to envisage leaving one's country, whilst political and institutional frustrations combine and lead citizens to consider taking part in violent demonstrations or even joining a revolution (aggression).},
  journal = {Societies},
  language = {en},
  number = {1}
}

@article{hartigUsingMultilevelRandom,
  title = {Using a Multilevel Random Item {{Rasch}} Model to Examine Item Difficulty Variance between Random Groups},
  author = {Hartig, Johannes and K{\"o}hler, Carmen and Naumann, Alexander},
  pages = {17},
  abstract = {In educational assessments, item difficulties are typically assumed to be invariant across groups (e.g., schools or countries). We refer to variances of item difficulties on the group level violating this assumption as random group differential item functioning (RG-DIF). We examine the performance of three methods to estimate RG-DIF: (

license: MIT

repository: atomashevic/website-at

license_type: permissive

repo_name: atomashevic/website-at

branch_name: refs/heads/master

extension: bib