text:
@article{abdul-rahmanSupportingTrustVirtual2000,
  title = {Supporting Trust in Virtual Communities},
  author = {{Abdul-Rahman}, A. and Hailes, S.},
  year = {2000},
  doi = {10.1109/HICSS.2000.926814},
  abstract = {At any given time, the stability of a community depends on the right balance of trust and distrust. Furthermore, we face information overload, increased uncertainty and risk taking as a prominent feature of modern living. As members of society, we cope with these complexities and uncertainties by relying trust, which is the basis of all social interactions. Although a small number of trust models have been proposed for the virtual medium, we find that they are largely impractical and artificial. In this paper we provide and discuss a trust model that is grounded in real-world social trust characteristics, and based on a reputation mechanism, or word-of-mouth. Our proposed model allows agents to decide which other agents' opinions they trust more and allows agents to progressively tune their understanding of another agent's subjective recommendations.},
  file = {/home/aleksandar/Zotero/storage/HGTPYZPA/Abdul-Rahman_Hailes_2000_Supporting trust in virtual communities2.pdf;/home/aleksandar/Zotero/storage/QXXZ6N2W/Abdul-Rahman_Hailes_2000_Supporting trust in virtual communities.pdf},
  journal = {Proceedings of the 33rd Annual Hawaii International Conference on System Sciences},
  keywords = {DONE,TODO}
}

@inproceedings{abererManagingTrustPeer2peer2001,
  title = {Managing Trust in a Peer-2-Peer Information System},
  booktitle = {Proceedings of the Tenth International Conference on {{Information}} and Knowledge Management},
  author = {Aberer, Karl and Despotovic, Zoran},
  year = {2001},
  month = oct,
  pages = {310--317},
  publisher = {{Association for Computing Machinery}},
  address = {{New York, NY, USA}},
  doi = {10.1145/502585.502638},
  abstract = {Managing trust is a problem of particular importance in peer-to-peer environments where one frequently encounters unknown agents. Existing methods for trust management, that are based on reputation, focus on the semantic properties of the trust model. They do not scale as they either rely on a central database or require to maintain global knowledge at each agent to provide data on earlier interactions. In this paper we present an approach that addresses the problem of reputation-based trust management at both the data management and the semantic level. We employ at both levels scalable data structures and algorithms that require no central control and allow to assess trust by computing an agents reputation from its former interactions with other agents. Thus the meethod can be implemented in a peer-to-peer environment and scales well for very large numbers of participants. We expect that scalable methods for trust management are an important factor, if fully decentralized peer-to-peer systems should become the platform for more serious applications than simple file exchange.},
  file = {/home/aleksandar/Documents/Zotero/Aberer_Despotovic/Aberer_Despotovic_2001_Managing trust in a peer-2-peer information system.pdf},
  isbn = {978-1-58113-436-0},
  series = {{{CIKM}} '01}
}

@article{abou-chadiHowPartiesReact2020,
  title = {How {{Parties React}} to {{Voter Transitions}}},
  author = {{Abou-Chadi}, Tarik and Stoetzer, Lukas F.},
  year = {2020},
  month = apr,
  pages = {1--6},
  issn = {0003-0554, 1537-5943},
  doi = {10.1017/S0003055420000155},
  abstract = {Abstract             This letter investigates how voter transitions between parties affect parties' policy positioning. While a growing literature investigates the role of election results as signals for parties' policy adaption, it has mostly focused on vote changes of individual parties. However, parties do not know only whether they have won or lost in an election; they also have detailed information on which parties they won votes from and which parties they lost votes to. We make two arguments about how voter transitions should affect the strategic policy choices of political parties. First, when a party has lost votes to another party it will adapt its policy positions toward that party. Second, parties that have overall lost more votes become more likely to adapt their positions. Making use of a data set on individual voter transitions and party positions we can demonstrate that voter transitions indeed affect parties' competitive behavior.},
  file = {/home/aleksandar/Dropbox/Zotero/Abou-Chadi_Stoetzer/Abou-Chadi_Stoetzer_2020_How Parties React to Voter Transitions.pdf},
  journal = {American Political Science Review},
  language = {en}
}

@article{aboutalebSparseCovarianceEstimation2020,
  title = {Sparse {{Covariance Estimation}} in {{Logit Mixture Models}}},
  author = {Aboutaleb, Youssef M. and Danaf, Mazen and Xie, Yifei and {Ben-Akiva}, Moshe},
  year = {2020},
  month = jan,
  abstract = {This paper introduces a new data-driven methodology for estimating sparse covariance matrices of the random coefficients in logit mixture models. Researchers typically specify covariance matrices in logit mixture models under one of two extreme assumptions: either an unrestricted full covariance matrix (allowing correlations between all random coefficients), or a restricted diagonal matrix (allowing no correlations at all). Our objective is to find optimal subsets of correlated coefficients for which we estimate covariances. We propose a new estimator, called MISC, that uses a mixed-integer optimization (MIO) program to find an optimal block diagonal structure specification for the covariance matrix, corresponding to subsets of correlated coefficients, for any desired sparsity level using Markov Chain Monte Carlo (MCMC) posterior draws from the unrestricted full covariance matrix. The optimal sparsity level of the covariance matrix is determined using out-of-sample validation. We demonstrate the ability of MISC to correctly recover the true covariance structure from synthetic data. In an empirical illustration using a stated preference survey on modes of transportation, we use MISC to obtain a sparse covariance matrix indicating how preferences for attributes are related to one another.},
  archivePrefix = {arXiv},
  eprint = {2001.05034},
  eprinttype = {arxiv},
  journal = {arXiv:2001.05034 [econ, stat]},
  language = {en},
  primaryClass = {econ, stat}
}

@article{acharouiUsingLatentClass2020,
  title = {Using {{Latent Class Analysis}} to {{Identify Political Behavior}} of {{Moroccan Citizens}} on {{Social Media}}},
  author = {Acharoui, Zakia and Alaoui, Altaf and Azhari, Mourad and Abarda, Abdallah and Ettaki, Badia},
  year = {2020},
  volume = {9},
  pages = {11},
  abstract = {The high use of social media has led to a new form of political involvement and participation. In this paper, we use Latent Class Analysis to identify participants' behavior regarding political participation and engagement based on the nature of their interaction on social media. The LCA findings reveal three statistically distinct and behavioral classes regarding political interaction on social media. The profiles were ranged from `Activist' that show more engagement in political activity, such as following candidates and political parties, posting and participating in discussions related to economic, social or political issues or, encouraging others to debate their point of view, to `Agitator' and `Outsider' profiles that show a low probability of interacting on social media and engaging in political actions. The LCA technique has provided meaningful and distinct information on the participants' political profile than clustering classical techniques.},
  language = {en},
  number = {6}
}

@article{acharyaEconomicFoundationsTerritorial,
  title = {Economic {{Foundations}} of the {{Territorial State System}}},
  author = {Acharya, Avidit and Lee, Alexander},
  doi = {10.1111/ajps.12379},
  abstract = {{$<$}div class="abstract-group"{$>$}    {$<$}section class="article-section article-section\_\_abstract" lang="en" data-lang="en" id="section-1-en"{$>$}       {$<$}h3 class="article-section\_\_header main abstractlang\_en main"{$>$}Abstract{$<$}/h3{$>$}       {$<$}div class="article-section\_\_content en main"{$>$}                              {$<$}p{$>$}The contemporary world is organized into a system of territorial states in which rulers             exercise authority inside clearly defined boundaries and recognize the authority of             other rulers outside those boundaries. We develop a model to explain how the major             economic and military developments in Europe starting in the fifteenth century contributed             to the development of this system. Our model rationalizes the system as an economic             cartel in which self-interested and forward-looking rulers maintain high tax revenues             by reducing competition in the ``market for governance.''          {$<$}/p{$>$}},
  journal = {American Journal of Political Science}
}

@article{acharyaEconomicFoundationsTerritoriala,
  title = {Economic {{Foundations}} of the {{Territorial State System}}},
  author = {Acharya, Avidit and Lee, Alexander},
  doi = {10.1111/ajps.12379},
  abstract = {{$<$}div class="abstract-group"{$>$}    {$<$}section class="article-section article-section\_\_abstract" lang="en" data-lang="en" id="section-1-en"{$>$}       {$<$}h3 class="article-section\_\_header main abstractlang\_en main"{$>$}Abstract{$<$}/h3{$>$}       {$<$}div class="article-section\_\_content en main"{$>$}                              {$<$}p{$>$}The contemporary world is organized into a system of territorial states in which rulers             exercise authority inside clearly defined boundaries and recognize the authority of             other rulers outside those boundaries. We develop a model to explain how the major             economic and military developments in Europe starting in the fifteenth century contributed             to the development of this system. Our model rationalizes the system as an economic             cartel in which self-interested and forward-looking rulers maintain high tax revenues             by reducing competition in the ``market for governance.''          {$<$}/p{$>$}},
  journal = {American Journal of Political Science}
}

@book{achenDemocracyRealistsWhy2016,
  title = {Democracy for Realists: Why Elections Do Not Produce Responsive Government},
  shorttitle = {Democracy for Realists},
  author = {Achen, Christopher H. and Bartels, Larry M.},
  year = {2016},
  publisher = {{Princeton University Press}},
  address = {{Princeton}},
  isbn = {978-0-691-16944-6},
  lccn = {JK1726 .A35 2016},
  series = {Princeton {{Studies}} in {{Political Behavior}}}
}

@article{aczelDiscussionPointsBayesian2020,
  title = {Discussion Points for {{Bayesian}} Inference},
  author = {Aczel, Balazs and Hoekstra, Rink and Gelman, Andrew and Wagenmakers, Eric-Jan and Klugkist, Irene G. and Rouder, Jeffrey N. and Vandekerckhove, Joachim and Lee, Michael D. and Morey, Richard D. and Vanpaemel, Wolf and Dienes, Zoltan and van Ravenzwaaij, Don},
  year = {2020},
  month = jan,
  pages = {1--3},
  issn = {2397-3374},
  doi = {10.1038/s41562-019-0807-z},
  abstract = {Why is there no consensual way of conducting Bayesian analyses? We present a summary of agreements and disagreements of the authors on several discussion points regarding Bayesian inference. We also provide a thinking guideline to assist researchers in conducting Bayesian inference in the social and behavioural sciences.},
  copyright = {2020 Springer Nature Limited},
  journal = {Nature Human Behaviour},
  language = {en}
}

@inproceedings{adahaliApplicationBenfordLaw2020,
  title = {Application of the {{Benford}}'s Law to {{Social}} Bots and {{Information Operations}} Activities},
  booktitle = {2020 {{International Conference}} on {{Cyber Situational Awareness}}, {{Data Analytics}} and {{Assessment}} ({{CyberSA}})},
  author = {{adahali}, Lale M and Hall, Margeret},
  year = {2020},
  month = jun,
  pages = {1--8},
  publisher = {{IEEE}},
  address = {{Dublin, Ireland}},
  doi = {10.1109/CyberSA49311.2020.9139709},
  abstract = {Benford's law shows the pattern of behavior in normal systems. It states that in natural systems digits' frequency have a certain pattern such that the occurrence of first digits in numbers are unevenly distributed. In systems with natural behavior, numbers begin with a "1" are more common than numbers beginning with "9". It implies that if the distribution of first digits deviate from the expected distribution, it is indicative of fraud. It has many applications in forensic accounting, stock markets, finding abnormal data in survey data, and natural science. We investigate whether social media bots and Information Operations activities are conformant to the Benford's law. Our results showed that bots' behavior adhere to Benford's law, suggesting that using this law helps in detecting malicious online automated accounts and their activities on social media. However, activities related to Information Operations did not show consistency in regards to Benford's law. Our findings shed light on the importance of examining regular and anomalous online behavior to avoid malicious and contaminated content on social media.},
  file = {/home/aleksandar/Zotero/storage/KHWM9524/adahali and Hall - 2020 - Application of the Benford’s law to Social bots an.pdf;/home/aleksandar/Zotero/storage/64NZ2YGE/9139709.html},
  isbn = {978-1-72816-690-2},
  language = {en}
}

@inproceedings{adaliMeasuringBehavioralTrust2010,
  title = {Measuring Behavioral Trust in Social Networks},
  booktitle = {2010 {{IEEE International Conference}} on {{Intelligence}} and {{Security Informatics}}},
  author = {Adali, Sibel and Escriva, Robert and Goldberg, Mark K. and Hayvanovych, Mykola and {Magdon-Ismail}, Malik and Szymanski, Boleslaw K. and Wallace, William A. and Williams, Gregory},
  year = {2010},
  month = may,
  pages = {150--152},
  doi = {10.1109/ISI.2010.5484757},
  abstract = {Trust is an important yet complex and little understood aspect of the dyadic relationship between two entities. Trust plays an important role in the formation of coalitions in social networks and in determining how high value of information flows through the network. We present algorithmically quantifiable measures of trust based on communication behavior. We propose that trust results in likely communication behaviors which are statistically different from random communications; detecting these trust-like behaviors allows us to develop a quantitative measure of who trusts whom in the network. We develop algorithms to efficiently compute such behavioral trust and validate these measures on the Twitter network.},
  file = {/home/aleksandar/Documents/Zotero/Adali et al/Adali et al_2010_Measuring behavioral trust in social networks.pdf;/home/aleksandar/Documents/Zotero/Adali et al/Notes.pdf;/home/aleksandar/Zotero/storage/AP6H9XFQ/5484757.html}
}

@article{adamczykExaminingPublicOpinion2019,
  title = {Examining {{Public Opinion About LGBTQ}}-{{Related Issues}} in the {{United States}} and {{Across Multiple Nations}}},
  author = {Adamczyk, Amy and Liao, Yen-Chiao},
  year = {2019},
  month = jul,
  volume = {45},
  pages = {401--423},
  issn = {0360-0572, 1545-2115},
  doi = {10.1146/annurev-soc-073018-022332},
  abstract = {Over the last three decades, many countries across the world, including the United States, have experienced major increases in support for LGBTQ (lesbian, gay, bisexual, transgender, and queer) individuals and related issues. In partial relation to these changes, multiple studies have examined the factors shaping public opinion. In this review, we focus on four major areas of research on public opinion in this field of study. First, we assess the terms that scholars typically use when examining attitudes and highlight the areas of public opinion research that have received the most attention. Second, we focus on the data and measurement challenges related to examining attitudes in the United States and across many nations. Third, we consider how and why attitudes and related laws have changed over time and across nations. Finally, we discuss the major micro and macro empirical forces that influence and the theoretical explanations for why there are such differences in attitudes. We end by offering several suggestions for future research.},
  journal = {Annual Review of Sociology},
  language = {en},
  number = {1}
}

@article{adamczykPlaceMattersContextualizing2016,
  title = {Place Matters: {{Contextualizing}} the Roles of Religion and Race for Understanding {{Americans}}' Attitudes about Homosexuality},
  shorttitle = {Place Matters},
  author = {Adamczyk, Amy and Boyd, Katharine A. and Hayes, Brittany E.},
  year = {2016},
  month = may,
  volume = {57},
  pages = {1--16},
  issn = {0049-089X},
  doi = {10.1016/j.ssresearch.2016.02.001},
  abstract = {As laws and policies related to homosexuality have evolved, Americans' attitudes have also changed. Race and religion have been established as important indicators of feelings about homosexuality. However, researchers have given almost no attention to how county characteristics shape Americans' attitudes. Using Hierarchical Linear Modeling techniques, we examine how personal characteristics and the religious and racial context of a county shape feelings about homosexuality drawing on data from the American National Election Survey and information about where respondents reside. We find that African Americans initially appear less tolerant than other racial groups, until we account for the geographical distribution of attitudes across the nation. Additionally, once we consider religious involvement, strength of belief, and religious affiliation African Americans appear to have warmer feelings about homosexuality than whites. Drawing on the moral communities' hypothesis, we also find that the strength of religiosity amongst county residents heightens the influence of personal religious beliefs on disapproving attitudes. There is also a direct effect of the proportion conservative Protestant, whereby people of all faiths have cooler attitudes towards homosexual individuals when they reside in a county with a higher proportion of conservative Protestants. Finally, we do not find any evidence for an African American cultural influence on attitudes.},
  file = {/home/aleksandar/Zotero/storage/8Q9M6G4W/S0049089X16000314.html},
  journal = {Social Science Research},
  language = {en}
}

@article{adolfsenMultipleDimensionsAttitudes2010,
  title = {Multiple Dimensions of Attitudes about Homosexuality: Development of a Multifaceted Scale Measuring Attitudes toward Homosexuality},
  shorttitle = {Multiple Dimensions of Attitudes about Homosexuality},
  author = {Adolfsen, Anna and Iedema, Jurjen and Keuzenkamp, Saskia},
  year = {2010},
  volume = {57},
  pages = {1237--1257},
  issn = {1540-3602},
  doi = {10.1080/00918369.2010.517069},
  abstract = {Attitudes toward homosexuality are complex. To get a comprehensive view on the attitudes of people, different dimensions need to be included in research. Based on a review of the literature, we distinguish five dimensions: acceptance of homosexuality in a general sense; attitude toward equal rights; reactions to homosexuality "at close quarters"; reactions to homosexuality in public; and so-called modern homonegativity. In a study on a representative sample of Dutch Defence personnel (N = 1,607) we tested this model. Structural equation modeling of several items measuring the attitude toward homosexuality offers a six factor solution. These six factors are more or less comparable to the five dimensions we distinguished. The dimension "reactions to homosexuality at close quarters" is, however, empirically split in a dimension on affective reactions to homosexuality and homosexual persons in general and a dimension on affective reaction to homosexual friends or acquaintances.},
  journal = {Journal of Homosexuality},
  language = {eng},
  number = {10},
  pmid = {21058145}
}

@misc{adornoKulturnaIndustrija2020,
  title = {Kulturna {{Industrija}}},
  author = {Adorno and Horkhajmer},
  year = {2020},
  file = {/home/aleksandar/Dropbox/Zotero/Adorno_Horkhajmer/Adorno_Horkhajmer_2020_Kulturna Industrija.pdf}
}

@book{AdvancesSociologyTrust2020,
  title = {Advances in the {{Sociology}} of {{Trust}} and {{Cooperation}}: {{Theory}}, {{Experiments}}, and {{Field Studies}}},
  shorttitle = {Advances in the {{Sociology}} of {{Trust}} and {{Cooperation}}},
  year = {2020},
  month = oct,
  publisher = {{De Gruyter}},
  abstract = {{$<$}p{$>$} The problem of cooperation and social order is one of the core issues in the social sciences. The key question is how humans, groups, institutions, and countries can avoid or overcome the collective good dilemmas that could lead to a Hobbesian "war of all against all". Using the general set of social dilemmas as a paradigmatic example, rigorous formal analysis can stimulate scientific progress in several ways. {$<$}/p{$>$}  {$<$}p{$>$} The book, consisting of original articles, provides state of the art examples of research along these lines: theoretical, experimental, and field studies on trust and cooperation. The theoretical work covers articles on trust and control, reputation formation, and paradigmatic articles on the benefits and caveats of abstracting reality into models. The experimental articles treat lab based tests of models of trust and reputation, and the effects of the social and institutional embeddedness on behavior in cooperative interactions and possibly emerging inequalities. The field studies test these models in applied settings such as cooperation between organizations, informal care, and different kinds of collaboration networks. {$<$}/p{$>$}  {$<$}p{$>$} The book will be exemplary for rigorous sociology and social sciences more in general in a variety of ways: {$<$}/p{$>$}  {$<$}ul{$>$}   {$<$}p{$>$} {$<$}/p{$>$}   {$<$}li{$>$} There is a focus on effects of social conditions, in particular different forms of social and institutional embeddedness, on social outcomes. Theorizing about and testing of effects of social contexts on individual and group outcomes is one of the main aims of sociological research. {$<$}/li{$>$}   {$<$}p{$>$} {$<$}/p{$>$}   {$<$}p{$>$} {$<$}/p{$>$}   {$<$}li{$>$} Modelling efforts include formal explications of micro-macro links that are typically easily overlooked when argumentation is intuitive and impressionistic {$<$}/li{$>$}   {$<$}p{$>$} {$<$}/p{$>$}   {$<$}p{$>$} {$<$}/p{$>$}   {$<$}li{$>$} Extensive attention is paid to unintended effects of intentional behavior, another feature that is a direct consequence of formal theoretical modelling and in-depth data-analyses of the social processes. {$<$}/li{$>$}   {$<$}p{$>$} {$<$}/p{$>$}   {$<$}p{$>$} {$<$}/p{$>$}   {$<$}li{$>$} By combining different empirical methods on the same questions, essentially the book sets forth a mixed-method design across chapters, allowing for a more convincing body of evidence per underlying question {$<$}/li{$>$}   {$<$}p{$>$} {$<$}/p{$>$}   {$<$}p{$>$} {$<$}/p{$>$}   {$<$}li{$>$} Some theoretical contributions re-evaluate what has been learned from the experimental and field results about the strengths and weaknesses of the earlier theoretical propositions, and extend the theory in light of these findings. {$<$}/li{$>$}   {$<$}p{$>$} {$<$}/p{$>$}  {$<$}/ul{$>$}  {$<$}strong{$><$}/strong{$>$}  {$<$}p{$>$} {$<$}/p{$>$}},
  file = {/home/aleksandar/Zotero/storage/ABM869QU/2020_Advances in the Sociology of Trust and Cooperation.pdf;/home/aleksandar/Zotero/storage/Q9XW74I8/565441.html},
  isbn = {978-3-11-064749-5},
  journal = {Advances in the Sociology of Trust and Cooperation},
  language = {en}
}

@article{ahsanhabibHowDoesConformity2020,
  title = {How Does Conformity Promote the Enhancement of Cooperation in the Network Reciprocity in Spatial Prisoner's Dilemma Games?},
  author = {Ahsan Habib, Md. and Tanaka, Masaki and Tanimoto, Jun},
  year = {2020},
  month = sep,
  volume = {138},
  pages = {109997},
  issn = {0960-0779},
  doi = {10.1016/j.chaos.2020.109997},
  abstract = {In line with more enhanced network reciprocity, we built a new spatial prisoner's dilemma (SPD) game considering conformity with presumption of lattice for underlying network and pairwise Fermi (PW-Fermi) for update rule. The key protocol is that a neighbor with more weight resulting from the conformity would be more likely selected as a pairwise opponent in the PW-Fermi updating process instead of random selection the conventional model presuming. A series of systematic simulations confirms that our model realizes more enhanced network reciprocity than the conventional SPD model. We elucidated its mechanism by means of considering on the concept of END period (meaning an initial period in which the global-cooperation fraction decreases from its initial value) and EXP periods (meaning the period following to END period in which global-cooperation increases) that substantially explaining how cooperative clusters survive in initial period and extend to defective zones afterwards.},
  file = {/home/aleksandar/Documents/Zotero/Ahsan Habib et al/Ahsan Habib et al_2020_How does conformity promote the enhancement of cooperation in the network.pdf;/home/aleksandar/Zotero/storage/C5PC9GRF/S0960077920303969.html},
  journal = {Chaos, Solitons \& Fractals},
  language = {en}
}

@book{ahujaNetworkFlowsTheory1993,
  title = {Network Flows: Theory, Algorithms, and Applications},
  shorttitle = {Network Flows},
  author = {Ahuja, Ravindra K. and Magnanti, Thomas L. and Orlin, James B.},
  year = {1993},
  publisher = {{Prentice Hall}},
  address = {{Englewood Cliffs, N.J}},
  isbn = {978-0-13-617549-0},
  lccn = {T57.85 .A37 1993}
}

@article{aidaPolarizationModelOnline2020,
  title = {Polarization {{Model}} of {{Online Social Networks Based}} on the {{Concept}} of {{Spontaneous Symmetry Breaking}}},
  author = {Aida, Masaki and Hashizume, Ayako and Takano, Chisa and Murata, Masayuki},
  year = {2020},
  month = nov,
  abstract = {The spread of information networks has not only made it easier for people to access a variety of information sources but also greatly enhanced the ability of individuals to disseminate information. Unfortunately, however, the problem of slander in online social networks shows that the evolving information network environment does not necessarily support mutual understanding in society. Since information with particular bias is distributed only to those communities that prefer it, the division of society into various opposing groups is strengthened. This phenomenon is called polarization. It is necessary to understand the mechanism of polarization to establish technologies that can counter polarization. This paper introduces a fundamental model for understanding polarization that is based on the concept of spontaneous symmetry breaking; our starting point is the oscillation model that describes user dynamics in online social networks.},
  archivePrefix = {arXiv},
  eprint = {2011.05393},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/L84FE6TL/Aida et al. - 2020 - Polarization Model of Online Social Networks Based.pdf},
  journal = {arXiv:2011.05393 [physics, physics:quant-ph]},
  keywords = {94-06,Computer Science - Social and Information Networks,Physics - Physics and Society,Quantum Physics},
  language = {en},
  primaryClass = {physics, physics:quant-ph}
}

@article{aidaPolarizationModelOnline2020a,
  title = {Polarization {{Model}} of {{Online Social Networks Based}} on the {{Concept}} of {{Spontaneous Symmetry Breaking}}},
  author = {Aida, Masaki and Hashizume, Ayako and Takano, Chisa and Murata, Masayuki},
  year = {2020},
  month = nov,
  abstract = {The spread of information networks has not only made it easier for people to access a variety of information sources but also greatly enhanced the ability of individuals to disseminate information. Unfortunately, however, the problem of slander in online social networks shows that the evolving information network environment does not necessarily support mutual understanding in society. Since information with particular bias is distributed only to those communities that prefer it, the division of society into various opposing groups is strengthened. This phenomenon is called polarization. It is necessary to understand the mechanism of polarization to establish technologies that can counter polarization. This paper introduces a fundamental model for understanding polarization that is based on the concept of spontaneous symmetry breaking; our starting point is the oscillation model that describes user dynamics in online social networks.},
  archivePrefix = {arXiv},
  eprint = {2011.05393},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Zotero/storage/BY8M7R4T/Aida et al. - 2020 - Polarization Model of Online Social Networks Based.pdf},
  journal = {arXiv:2011.05393 [physics, physics:quant-ph]},
  keywords = {94-06,Computer Science - Social and Information Networks,Physics - Physics and Society,Quantum Physics},
  language = {en},
  primaryClass = {physics, physics:quant-ph}
}

@article{akanbiModelComparisonApplication2020,
  title = {On {{Model Comparison}}: {{Application}} of {{Savage}}-{{Dickey Density Ratio}} to {{Bayes Factor}}},
  shorttitle = {On {{Model Comparison}}},
  author = {Akanbi, Olawale B. and Olubusoye, Olusanya E. and Babatunde, Samuel A.},
  year = {2020},
  month = feb,
  pages = {25--46},
  issn = {2582-0230},
  doi = {10.9734/ajpas/2020/v6i330162},
  file = {/home/aleksandar/Zotero/storage/2R3WASW9/30162.html},
  journal = {Asian Journal of Probability and Statistics},
  language = {en-US}
}

@article{akbarQuantumComputingBased2020,
  title = {Towards Quantum Computing Based Community Detection},
  author = {Akbar, Sana and Saritha, Sri Khetwat},
  year = {2020},
  month = nov,
  volume = {38},
  pages = {100313},
  issn = {1574-0137},
  doi = {10.1016/j.cosrev.2020.100313},
  abstract = {Over the past decade, social network analysis has earned pivotal eminence in the area of web mining and information retrieval. Community detection, being the indispensable part of social network analysis; has garnered far reaching usance in business analytics, healthcare, security, research and policy making. With the embodiment of copious domains to social networks and unprecedented rise in the data \textemdash{} produced, accessed and stored globally; the task of handling the unpredictable, dynamic and ever evolving topological nature of social networks has become arduous. In this regard, quantum computing (QC) has emerged as the most promising trailblazer guaranteeing unprecedented data storage and manipulation capabilities by- dynamic allocation of cluster size and architecture, quantum parallelism, reduced parameter dependency, etc. QC based algorithms have registered exponential speedup over many classical problems with better efficiency and abated time complexity; apart from solving NP-hard problems that were unrealizable classically. Accordingly, a comprehensive literature survey has been presented for social network analysis and community detection highlighting the limitations prevalent in the current technologies. A brief insight into quantum computing and its proficiency in rendering to larger storage systems has been presented; as a solution to the inherent problems present in the existing community detection approaches. A systematic account of quantum computing based community detection techniques has been summarized and discussed as a more prudent future alternative to social network analysis and community detection. Lastly, complexity analysis and modularity based comparison of QC based algorithms with other state of the art algorithms has been carried out to establish the supremacy of quantum algorithms in community detection.},
  file = {/home/aleksandar/Zotero/storage/ZSW3HSZU/S1574013720304135.html},
  journal = {Computer Science Review},
  keywords = {Community detection,Quantum annealing (QA),Quantum computing,Quantum machine learning,Social network analysis},
  language = {en}
}

@article{akcoraGraphBootQuantifyingUncertainty2019,
  title = {{{GraphBoot}}: {{Quantifying Uncertainty}} in {{Node Feature Learning}} on {{Large Networks}}},
  shorttitle = {{{GraphBoot}}},
  author = {Akcora, Cuneyt and Gel, Yulia and Kantarcioglu, Murat and Lyubchich, Vyacheslav and Thuraisingam, Bhavani},
  year = {2019},
  pages = {1--1},
  issn = {1041-4347, 1558-2191, 2326-3865},
  doi = {10.1109/TKDE.2019.2925355},
  journal = {IEEE Transactions on Knowledge and Data Engineering}
}

@article{albertStructuralVulnerabilityNorth2004,
  title = {Structural Vulnerability of the {{North American}} Power Grid},
  author = {Albert, R{\'e}ka and Albert, Istv{\'a}n and Nakarado, Gary L.},
  year = {2004},
  month = feb,
  volume = {69},
  issn = {1539-3755, 1550-2376},
  doi = {10.1103/PhysRevE.69.025103},
  journal = {Physical Review E},
  language = {en},
  number = {2}
}

@book{aleksandrovMathematicsItsContent1999,
  title = {Mathematics, Its Content, Methods, and Meaning},
  editor = {Aleksandrov, A. D. and Kolmogorov, A. N. and Lavrent'ev, M. A.},
  year = {1999},
  publisher = {{Dover Publications}},
  address = {{Mineola, N.Y}},
  isbn = {978-0-486-40916-0},
  language = {eng},
  lccn = {QA36 .M2913 1999}
}

@article{alexanderPollBasedConjugatePrior,
  title = {Poll-{{Based Conjugate Prior Models}} for the {{Prediction}} of {{United States Presidential Elections}}},
  author = {Alexander, Brittany and Ellingson, Leif},
  pages = {20},
  abstract = {A previous Bayesian model used to predict the 2008, 2012, and 2016 United States Presidential Elections using only poll data resulted in nearly identical electoral college predictions to FiveThirtyEight, and 95.329\% relative accuracy to the FiveThirtyEight Polls Plus model in terms of root mean square error of the predictions of the two major candidates. The previous model used poll data from either another single similar state or national polls to create prior distributions and used the MLE estimators to fit the model. We present new models with minor differences that are used on the same data used in the previous model. The new models now pool the polls together from other states in the regions and uses the pooled estimates as the prior instead of relying on poll data from one state. The new models compare the beta and Gaussian conjugate prior and use three different methods to reassign undecided voters, and either updates iteratively or pools the polls together and performs the calculation once. We also provide a variety of models to serve as comparison for the model's accuracy such as a noninformative model, and polls only model.},
  language = {en}
}

@article{alexopoulosBayesianForecastingMortality,
  ids = {alexopoulosBayesianForecastingMortalitya},
  title = {Bayesian Forecasting of Mortality Rates by Using Latent {{Gaussian}} Models},
  author = {Alexopoulos, Angelos and Dellaportas, Petros and Forster, Jonathan J.},
  doi = {10.1111/rssa.12422},
  abstract = {{$<$}style{$>$}             .inline-equation \{             overflow-x:auto;             \}         {$<$}/style{$><$}article{$>$}        {$<$}div class="abstract-group"{$>$}       {$<$}section class="article-section article-section\_\_abstract" lang="en" data-lang="en" id="section-1-en"{$>$}          {$<$}h2 id="d10056009" class="article-section\_\_header section\_\_title main abstractlang\_en main"{$>$}Abstract{$<$}/h2{$>$}          {$<$}div class="article-section\_\_content en main"{$>$}                                       {$<$}p{$>$}We provide forecasts for mortality rates by using two different approaches. First we employ dynamic non-linear logistic models based on the Heligman\textendash Pollard formula. Second, we assume that the dynamics of the mortality rates can be modelled through a Gaussian Markov random field. We use efficient Bayesian methods to estimate the parameters and the latent states of the models proposed. Both methodologies are tested with past data and are used to forecast mortality rates both for large (UK and Wales) and small (New Zealand) populations up to 21 years ahead. We demonstrate that predictions for individual survivor functions and other posterior summaries of demographic and actuarial interest are readily obtained. Our results are compared with other competing forecasting methods.{$<$}/p{$>$}},
  journal = {Journal of the Royal Statistical Society. Series A, (Statistics in Society)}
}

@inproceedings{alipourfardCanYouTrust2018,
  title = {Can You {{Trust}} the {{Trend}}? {{Discovering Simpson}}'s {{Paradoxes}} in {{Social Data}}},
  shorttitle = {Can You {{Trust}} the {{Trend}}?},
  booktitle = {Proceedings of the {{Eleventh ACM International Conference}} on {{Web Search}} and {{Data Mining}}},
  author = {Alipourfard, Nazanin and Fennell, Peter G. and Lerman, Kristina},
  year = {2018},
  month = feb,
  pages = {19--27},
  publisher = {{Association for Computing Machinery}},
  address = {{New York, NY, USA}},
  doi = {10.1145/3159652.3159684},
  abstract = {We investigate how Simpson\guillemotright s paradox affects analysis of trends in social data. According to the paradox, the trends observed in data that has been aggregated over an entire population may be different from, and even opposite to, those of the underlying subgroups. Failure to take this effect into account can lead analysis to wrong conclusions. We present a statistical method to automatically identify Simpson\guillemotright s paradox in data by comparing statistical trends in the aggregate data to those in the disaggregated subgroups. We apply the approach to data from Stack Exchange, a popular question-answering platform, to analyze factors affecting answerer performance, specifically, the likelihood that an answer written by a user will be accepted by the asker as the best answer to his or her question. Our analysis confirms a known Simpson\guillemotright s paradox and identifies several new instances. These paradoxes provide novel insights into user behavior on Stack Exchange.},
  file = {/home/aleksandar/Zotero/storage/AN38CBYK/Alipourfard et al_2018_Can you Trust the Trend.pdf},
  isbn = {978-1-4503-5581-0},
  series = {{{WSDM}} '18}
}

@article{allamanisWhyWhenWhat2013,
  title = {Why, When, and What: {{Analyzing Stack Overflow}} Questions by Topic, Type, and Code},
  shorttitle = {Why, When, and What},
  author = {Allamanis, Miltiadis and Sutton, Charles},
  year = {2013},
  doi = {10.1109/MSR.2013.6624004},
  abstract = {Questions from Stack Overflow provide a unique opportunity to gain insight into what programming concepts are the most confusing. We present a topic modeling analysis that combines question concepts, types, and code. Using topic modeling, we are able to associate programming concepts and identifiers (like the String class) with particular types of questions, such as, ``how to perform encoding''.},
  file = {/home/aleksandar/Zotero/storage/2TES6BAB/Allamanis_Sutton_2013_Why, when, and what.pdf},
  journal = {2013 10th Working Conference on Mining Software Repositories (MSR)},
  keywords = {DONE}
}

@techreport{allcottPolarizationPublicHealth2020,
  title = {Polarization and {{Public Health}}: {{Partisan Differences}} in {{Social Distancing During}} the {{Coronavirus Pandemic}}},
  shorttitle = {Polarization and {{Public Health}}},
  author = {Allcott, Hunt and Boxell, Levi and Conway, Jacob and Gentzkow, Matthew and Thaler, Michael and Yang, David Y.},
  year = {2020},
  month = apr,
  address = {{Rochester, NY}},
  institution = {{Social Science Research Network}},
  abstract = {We study partisan differences in Americans' response to the COVID-19 pandemic. Political leaders and media outlets on the right and left have sent divergent messages about the severity of the crisis, which could impact the extent to which Republicans and Democrats engage in social distancing and other efforts to reduce disease transmission. We develop a simple model of a pandemic response with heterogeneous agents that clarifies the causes and consequences of heterogeneous responses. We use location data from a large sample of smartphones to show that areas with more Republicans engage in less social distancing, controlling for other factors including state policies, population density, and local COVID cases and deaths. We then present new survey evidence of significant gaps between Republicans and Democrats in beliefs about personal risk and the future path of the pandemic.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.},
  language = {en},
  number = {ID 3574415},
  type = {{{SSRN Scholarly Paper}}}
}

@book{alligoodChaosIntroductionDynamical2000,
  title = {Chaos: An Introduction to Dynamical Systems},
  shorttitle = {Chaos},
  author = {Alligood, Kathleen T. and Sauer, Tim D. and Yorke, James A.},
  year = {2000},
  edition = {Corr. 3. print},
  publisher = {{Springer}},
  address = {{New York, NY}},
  annotation = {OCLC: 248606567},
  isbn = {978-0-387-94677-1},
  language = {eng},
  series = {Textbooks in Mathematical Sciences}
}

@article{almaatouqAdaptiveSocialNetworks2020,
  title = {Adaptive Social Networks Promote the Wisdom of Crowds},
  author = {Almaatouq, Abdullah and {Noriega-Campero}, Alejandro and Alotaibi, Abdulrahman and Krafft, P. M. and Moussaid, Mehdi and Pentland, Alex},
  year = {2020},
  month = may,
  volume = {117},
  pages = {11379--11386},
  publisher = {{National Academy of Sciences}},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.1917687117},
  abstract = {Social networks continuously change as new ties are created and existing ones fade. It is widely acknowledged that our social embedding has a substantial impact on what information we receive and how we form beliefs and make decisions. However, most empirical studies on the role of social networks in collective intelligence have overlooked the dynamic nature of social networks and its role in fostering adaptive collective intelligence. Therefore, little is known about how groups of individuals dynamically modify their local connections and, accordingly, the topology of the network of interactions to respond to changing environmental conditions. In this paper, we address this question through a series of behavioral experiments and supporting simulations. Our results reveal that, in the presence of plasticity and feedback, social networks can adapt to biased and changing information environments and produce collective estimates that are more accurate than their best-performing member. To explain these results, we explore two mechanisms: 1) a global-adaptation mechanism where the structural connectivity of the network itself changes such that it amplifies the estimates of high-performing members within the group (i.e., the network ``edges'' encode the computation); and 2) a local-adaptation mechanism where accurate individuals are more resistant to social influence (i.e., adjustments to the attributes of the ``node'' in the network); therefore, their initial belief is disproportionately weighted in the collective estimate. Our findings substantiate the role of social-network plasticity and feedback as key adaptive mechanisms for refining individual and collective judgments.},
  chapter = {Social Sciences},
  copyright = {Copyright \textcopyright{} 2020 the Author(s). Published by PNAS.. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).},
  file = {/home/aleksandar/Documents/Zotero/Almaatouq et al/Almaatouq et al_2020_Adaptive social networks promote the wisdom of crowds.pdf;/home/aleksandar/Zotero/storage/G6T558IS/11379.html},
  isbn = {9781917687119},
  journal = {Proceedings of the National Academy of Sciences},
  language = {en},
  number = {21},
  pmid = {32393632}
}

@article{almaatouqEmpiricaVirtualLab2020,
  title = {Empirica: A Virtual Lab for High-Throughput Macro-Level Experiments},
  shorttitle = {Empirica},
  author = {Almaatouq, Abdullah and Becker, Joshua and Houghton, James P. and Paton, Nicolas and Watts, Duncan J. and Whiting, Mark E.},
  year = {2020},
  month = jun,
  abstract = {Virtual labs allow researchers to design high-throughput and macro-level experiments that are not feasible in traditional in-person physical lab settings. Despite the increasing popularity of online research, researchers still face many technical and logistical barriers when designing and deploying virtual lab experiments. While several platforms exist to facilitate the development of virtual lab experiments, they typically present researchers with a stark trade-off between usability and functionality. We introduce Empirica: a modular virtual lab that offers a solution to the usability-functionality trade-off by employing a "flexible defaults" design strategy. This strategy enables us to maintain complete "build anything" flexibility while offering a development platform that is accessible to novice programmers. Empirica's architecture is designed to allow for parameterizable experimental designs, re-usable protocols, and rapid development. These features will increase the accessibility of virtual lab experiments, remove barriers to innovation in experiment design, and enable rapid progress in the understanding of distributed human computation.},
  archivePrefix = {arXiv},
  eprint = {2006.11398},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Almaatouq et al/Almaatouq et al_2020_Empirica.pdf;/home/aleksandar/Zotero/storage/H3SHTGZU/2006.html},
  journal = {arXiv:2006.11398 [cs]},
  keywords = {DONE},
  primaryClass = {cs}
}

@article{almaatouqWhenSocialInfluence2020,
  title = {When Social Influence Promotes the Wisdom of Crowds},
  author = {Almaatouq, Abdullah and Rahimian, M. Amin and Alhajri, Abdulla},
  year = {2020},
  month = jun,
  abstract = {Questions regarding whether, and if so, under what conditions, groups exhibit ''crowd wisdom'' have spurred numerous studies in many disciplines, including management and organizational science, psychology, sociology, complex systems, and computer science. Substantial effort in previous research on these questions has focused on investigating the role of social influence in promoting the wisdom of the crowd or, conversely, leading the crowd astray. Specifically, many previous studies have sought to infer the importance of social influence network attributes (such as influence centralization) to explain the accuracy of collective estimates. In this paper, we argue that this approach is limited and can lead to inconsistent conclusions. Based on our theoretical analysis, numerical simulation, and reanalysis of four previously published experiments (which included a total of 4,002 human participants, organized in 131 independent groups), we demonstrate that the wisdom of crowds in estimation tasks depends on the interaction between the following two factors: (i) centralization of the social influence network, and (ii) the features of the estimation context---i.e., the distribution of the initial (pre-influence) estimates. Specifically, we find that centralized influence is desirable in situations where a crowd is predisposed to overestimation bias and/or have a high likelihood of committing egregious errors. By adopting a framework that integrates both the structure of social influence and the estimation context, we bring the previously conflicting results under one theoretical framework and clarify the effects of influence centralization on the quality of crowd wisdom.},
  archivePrefix = {arXiv},
  eprint = {2006.12471},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Dropbox/Zotero/Almaatouq et al/Almaatouq et al_2020_When social influence promotes the wisdom of crowds.pdf;/home/aleksandar/Zotero/storage/B6BCZC8H/2006.html},
  journal = {arXiv:2006.12471 [cs, stat]},
  primaryClass = {cs, stat}
}

@article{almeidaOptimalLeaderfollowingConsensus2020,
  title = {Optimal Leader-Following Consensus of Fractional Opinion Formation Models},
  author = {Almeida, Ricardo and Kamocki, Rafa{\l} and Malinowska, Agnieszka B. and Odzijewicz, Tatiana},
  year = {2020},
  month = jun,
  pages = {112996},
  issn = {0377-0427},
  doi = {10.1016/j.cam.2020.112996},
  abstract = {This paper deals with a control strategy enforcing consensus in a fractional opinion formation model with leadership, where the interaction rates between followers and the influence rate of the leader are functions of deviations of opinions between agents. The fractional-order derivative determines the impact of the memory during the opinion evolution. The problem of leader-following consensus control is cast in the framework of nonlinear optimal control theory. We study a finite horizon optimal control problem, in which deviations of opinions between agents and with respect to the leader are penalized along with the control that is applied only to the leader. The existence conditions for optimal consensus control are proved and necessary optimality conditions for the considered problem are derived. The results of the paper are illustrated by some examples.},
  journal = {Journal of Computational and Applied Mathematics},
  language = {en}
}

@book{almondComparativePoliticsDevelopmental1966,
  title = {Comparative Politics: {{A}} Developmental Approach},
  author = {Almond, G. and Powell, B.},
  year = {1966},
  publisher = {{Little and Brown}},
  address = {{Boston}}
}

@article{alraddadiRoleHomophilyOpinion2020,
  title = {The Role of Homophily in Opinion Formation among Mobile Agents},
  author = {Alraddadi, Enas E. and Allen, Stuart M. and Colombo, Gualtiero B. and Whitaker, Roger M.},
  year = {2020},
  month = jun,
  pages = {1--20},
  issn = {2475-1839, 2475-1847},
  doi = {10.1080/24751839.2020.1772614},
  abstract = {Understanding the evolution and spread of opinions within social groups gives important insight into areas such as public elections and marketing. We are specifically interested in how psychological theories of interpersonal influence may affect how individuals change their opinion through interactions with their peers, and apply Agent-Based Modelling to explore the factors that may affect the emergence of consensus. We investigate the coevolution of opinion and location by extending the Deffuant\textendash Weisbuch bounded confidence opinion model to include mobility inspired by the psychological theories of homophily and dissonance, where agents are attracted or repelled by their neighbours based on the agreement of their opinions. Based on wide experimentation, we characterize the time it takes to converge to a steady state and the local diversity of opinions that results, finding that homophily leads to drastic differences in the nature of consensus. We further extend our mobility model and add noise in order to check the model's robustness, finding that a number of opinion clusters survive even with high levels of noise.},
  file = {/home/aleksandar/Dropbox/Zotero/Alraddadi et al/Alraddadi et al_2020_The role of homophily in opinion formation among mobile agents.pdf},
  journal = {Journal of Information and Telecommunication},
  language = {en}
}

@inproceedings{alsahafyFastAlgorithmDistance2020,
  title = {Fast {{Algorithm}} for {{Distance Dynamics}}-{{Based Community Detection}}},
  booktitle = {Web {{Information Systems Engineering}} \textendash{} {{WISE}} 2020},
  author = {Alsahafy, Maram and Chang, Lijun},
  editor = {Huang, Zhisheng and Beek, Wouter and Wang, Hua and Zhou, Rui and Zhang, Yanchun},
  year = {2020},
  pages = {213--226},
  publisher = {{Springer International Publishing}},
  address = {{Cham}},
  doi = {10.1007/978-3-030-62005-9_16},
  abstract = {Community detection is a fundamental problem in graph-based data analytics. Among many models, the distance dynamics model proposed recently is shown to be able to faithfully capture natural communities that are of different sizes. However, the state-of-the-art algorithm AttractorAttractor\textbackslash mathsf \{Attractor\} for distance dynamics does not scale to graphs with large maximum vertex degrees, which is the case for large real graphs. In this paper, we aim to scale distance dynamics to large graphs. To achieve that, we propose a fast distance dynamics algorithm FDDFDD\textbackslash mathsf \{FDD\}. We show that FDDFDD\textbackslash mathsf \{FDD\} has a worst-case time complexity of O(T{$\cdot\gamma\cdot$}m)O(T{$\cdot\gamma\cdot$}m) \textbackslash mathcal\{O\}(T\textbackslash cdot \textbackslash gamma \textbackslash cdot m), where T is the number of iterations until convergence, {$\gamma\gamma\backslash$}gamma is a small constant, and m is the number of edges in the input graph. Thus, the time complexity of FDDFDD\textbackslash mathsf \{FDD\} does not depend on the maximum vertex degree. Moreover, we also propose optimization techniques to alleviate the dependency on T. We conduct extensive empirical studies on large real graphs and demonstrate the efficiency and effectiveness of FDDFDD\textbackslash mathsf \{FDD\}.},
  isbn = {978-3-030-62005-9},
  language = {en},
  series = {Lecture {{Notes}} in {{Computer Science}}}
}

@article{altenbuchingerGaussianMixedGraphical2019,
  title = {Gaussian and {{Mixed Graphical Models}} as (Multi-)Omics Data Analysis Tools},
  author = {Altenbuchinger, Michael and Weihs, Antoine and Quackenbush, John and J{\"o}rgen Grabe, Hans and Zacharias, Helena U.},
  year = {2019},
  month = oct,
  pages = {194418},
  issn = {1874-9399},
  doi = {10.1016/j.bbagrm.2019.194418},
  abstract = {Gaussian Graphical Models (GGMs) are tools to infer dependencies between biological variables. Popular applications are the reconstruction of gene, protein, and metabolite association networks. GGMs are an exploratory research tool that can be useful to discover interesting relations between genes (functional clusters) or to identify therapeutically interesting genes, but do not necessarily infer a network in the mechanistic sense. Although GGMs are well investigated from a theoretical and applied perspective, important extensions are not well known within the biological community. GGMs assume, for instance, multivariate normal distributed data. If this assumption is violated Mixed Graphical Models (MGMs) can be the better choice. In this review we provide the theoretical foundations of GGMs, present extensions such as MGMs or multi-class GGMs, and illustrate how those methods can provide insight in biological mechanisms. We summarize several applications and present user-friendly estimation software.},
  file = {/home/aleksandar/Zotero/storage/IF4AHDGM/S187493991930224X.html},
  journal = {Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms},
  language = {en}
}

@article{alvarezPayingAttentionInattentive2019,
  title = {Paying {{Attention}} to {{Inattentive Survey Respondents}}},
  author = {Alvarez, R. Michael and Atkeson, Lonna Rae and Levin, Ines and Li, Yimeng},
  year = {2019},
  month = apr,
  volume = {27},
  pages = {145--162},
  issn = {1047-1987, 1476-4989},
  doi = {10.1017/pan.2018.57},
  abstract = {Does attentiveness matter in survey responses? Do more attentive survey participants give higher quality responses? Using data from a recent online survey that identified inattentive respondents using instructed-response items, we demonstrate that ignoring attentiveness provides a biased portrait of the distribution of critical political attitudes and behavior. We show that this bias occurs in the context of both typical closed-ended questions and in list experiments. Inattentive respondents are common and are more prevalent among the young and less educated. Those who do not pass the trap questions interact with the survey instrument in distinctive ways: they take less time to respond; are more likely to report nonattitudes; and display lower consistency in their reported choices. Inattentiveness does not occur completely at random and failing to properly account for it may lead to inaccurate estimates of the prevalence of key political attitudes and behaviors, of both sensitive and more prosaic nature.},
  file = {/home/aleksandar/Zotero/storage/3MXT6VKE/BEDA4CF3245489645859E7E6B022E75A.html},
  journal = {Political Analysis},
  language = {en},
  number = {2}
}

@article{alvarezWhatOthersConsensus,
  title = {What about the Others? {{Consensus}} and Equilibria in the Presence of Self-Interest and Conformity in Social Groups},
  author = {Alvarez, Emiliano and Brida, Juan Gabriel},
  doi = {S0378437118314973},
  abstract = {{$<$}p{$>$}Publication date: Available online 7 December 2018{$<$}/p{$><$}p{$>$}\textbf{Source:} Physica A: Statistical Mechanics and its Applications{$<$}/p{$><$}p{$>$}Author(s): Emiliano Alvarez, Juan Gabriel Brida{$<$}/p{$><$}h5{$>$}Abstract{$<$}/h5{$><$}div{$><$}p{$>$}This paper analyses the decision-making processes of heterogeneous agents, when both individual preferences and group actions are taken into account. Under the assumptions of certain topologies of interactions and assuming cognitive and informational restrictions, an agent-based model is introduced to analyze the evolution of decisions over time. The results of the simulations show how social pressures can determine the relationship between individual and social preferences. Societies whose agents have strong individual preferences have outcomes with fragmentation processes that generates a higher number of groups. A minor importance of the individual preferences, results in a smaller proportion of individuals maximizing their individual utility. As well, the quantity of options available and the initial proportion of each alternative are significant variables to determine the proportion of individuals selecting a particular option. In addition, the study analyses the existence of equilibrium of the dynamical system. To this aim, the notion of metastable equilibria is introduced and linked to the dynamic analysis.{$<$}/p{$><$}/div{$>$}},
  journal = {Physica A: Statistical Mechanics and its Applications}
}

@article{alwinNumberResponseCategories2018,
  title = {Number of {{Response Categories}} and {{Reliability}} in {{Attitude Measurement}}},
  author = {Alwin, Duane F. and Baumgartner, Erin M. and Beattie, Brett A.},
  year = {2018},
  month = jun,
  volume = {6},
  pages = {212--239},
  issn = {2325-0984},
  doi = {10.1093/jssam/smx025},
  abstract = {Abstract.  Relying on data from three General Social Survey (GSS) panel studies, conducted in 2006/2008/2010, 2008/2010/2012, and 2010/2012/2014, and building o},
  file = {/home/aleksandar/Zotero/storage/KPXQ7JAP/4201741.html},
  journal = {Journal of Survey Statistics and Methodology},
  language = {en},
  number = {2}
}

@article{amaralEpidemiologicalModelVoluntary2020,
  title = {An Epidemiological Model with Voluntary Quarantine Strategies Governed by Evolutionary Game Dynamics},
  author = {Amaral, Marco A. and {de Oliveira}, Marcelo M. and Javarone, Marco A.},
  year = {2020},
  month = aug,
  abstract = {During pandemic events, strategies such as social distancing can be fundamental to curb viral spreading. Such actions can reduce the number of simultaneous infections and mitigate the disease spreading, which is relevant to the risk of a healthcare system collapse. Although these strategies can be suggested, their actual implementation may depend on the population perception of the disease risk. The current COVID-19 crisis, for instance, is showing that some individuals are much more prone than others to remain isolated, avoiding unnecessary contacts. With this motivation, we propose an epidemiological SIR model that uses evolutionary game theory to take into account dynamic individual quarantine strategies, intending to combine in a single process social strategies, individual risk perception, and viral spreading. The disease spreads in a population whose agents can choose between self-isolation and a lifestyle careless of any epidemic risk. The strategy adoption is individual and depends on the perceived disease risk compared to the quarantine cost. The game payoff governs the strategy adoption, while the epidemic process governs the agent's health state. At the same time, the infection rate depends on the agent's strategy while the perceived disease risk depends on the fraction of infected agents. Results show recurrent infection waves, which were seen in previous epidemic scenarios with quarantine. Notably, the risk perception is found to be fundamental for controlling the magnitude of the infection peak, while the final infection size is mainly dictated by the infection rates. Low awareness leads to a single and strong infection peak, while a greater disease risk leads to shorter, although more frequent, peaks. The proposed model spontaneously captures relevant aspects of a pandemic event, highlighting the fundamental role of social strategies.},
  archivePrefix = {arXiv},
  eprint = {2008.05979},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Amaral et al/Amaral et al_2020_An epidemiological model with voluntary quarantine strategies governed by.pdf;/home/aleksandar/Zotero/storage/X3TZPWSN/2008.html},
  journal = {arXiv:2008.05979 [physics, q-bio]},
  primaryClass = {physics, q-bio}
}

@article{amirjanovCooperativeCompetitiveMechanisms2020,
  title = {The Cooperative and Competitive Mechanisms of a Leader's Opinion Transmission},
  author = {Amirjanov, Adil},
  year = {2020},
  month = aug,
  pages = {2050127},
  publisher = {{World Scientific Publishing Co.}},
  issn = {0129-1831},
  doi = {10.1142/S0129183120501272},
  abstract = {The paper modeled a leader's opinion transmission in a population. The proposed model develops the cooperation agent-based continuous model in which the cooperation of individuals is based on the similarity of evolved ``tags'' which are relative to evolved tag-difference tolerances. In proposed model, an individual's opinion and the individual's tolerance are specified as variables in the model. During communication with each other and with a leader, the resources of individuals are incremented, if they are tolerable to the opinions of their opponents. An opinion formation in population is established by a cooperative process~\textemdash{} changing individual's opinion, if the individual is tolerable to the opinions of opponents, and by a competitive process~\textemdash{} copying opinions and tolerances of successful individuals who have higher resource. Numerical experiments have proven that the public opinion reached a consensus followed the leader's opinion.},
  file = {/home/aleksandar/Zotero/storage/Z5Z4V8NB/S0129183120501272.html},
  journal = {International Journal of Modern Physics C}
}

@article{amorosoPotentialEnergyComplex2020,
  title = {Potential Energy of Complex Networks: A Quantum Mechanical Perspective},
  shorttitle = {Potential Energy of Complex Networks},
  author = {Amoroso, Nicola and Bellantuono, Loredana and Pascazio, Saverio and Lombardi, Angela and Monaco, Alfonso and Tangaro, Sabina and Bellotti, Roberto},
  year = {2020},
  month = oct,
  volume = {10},
  pages = {18387},
  publisher = {{Nature Publishing Group}},
  issn = {2045-2322},
  doi = {10.1038/s41598-020-75147-w},
  abstract = {We propose a characterization of complex networks, based on the potential of an associated Schr\"odinger equation. The potential is designed so that the energy spectrum of the Schr\"odinger equation coincides with the graph spectrum of the normalized Laplacian. Crucial information is retained in the reconstructed potential, which provides a compact representation of the properties of the network structure. The median potential over several random network realizations, which we call ensemble potential, is fitted via a Landau-like function, and its length scale is found to diverge as the critical connection probability is approached from above. The ruggedness of the ensemble potential profile is quantified by using the Higuchi fractal dimension, which displays a maximum at the critical connection probability. This demonstrates that this technique can be successfully employed in the study of random networks, as an alternative indicator of the percolation phase transition. We apply the proposed approach to the investigation of real-world networks describing infrastructures (US power grid). Curiously, although no notion of phase transition can be given for such networks, the fractality of the ensemble potential displays signatures of criticality. We also show that standard techniques (such as the scaling features of the largest connected component) do not detect any signature or remnant of criticality.},
  copyright = {2020 The Author(s)},
  file = {/home/aleksandar/Documents/Zotero/Amoroso et al/Amoroso et al_2020_Potential energy of complex networks.pdf;/home/aleksandar/Zotero/storage/5QP6U2XW/s41598-020-75147-w.html},
  journal = {Scientific Reports},
  language = {en},
  number = {1}
}

@inproceedings{anagnostopoulosBiasedOpinionDynamics2020,
  title = {Biased {{Opinion Dynamics}}: {{When}} the {{Devil}} Is in the {{Details}}},
  shorttitle = {Biased {{Opinion Dynamics}}},
  booktitle = {Proceedings of the {{Twenty}}-{{Ninth International Joint Conference}} on {{Artificial Intelligence}}},
  author = {Anagnostopoulos, Aris and Becchetti, Luca and Cruciani, Emilio and Pasquale, Francesco and Rizzo, Sara},
  year = {2020},
  month = jul,
  pages = {53--59},
  publisher = {{International Joint Conferences on Artificial Intelligence Organization}},
  address = {{Yokohama, Japan}},
  doi = {10.24963/ijcai.2020/8},
  abstract = {We investigate opinion dynamics in multi-agent networks when there exists a bias toward one of two possible opinions; for example, reflecting a status quo vs a superior alternative. Starting with all agents sharing an initial opinion representing the status quo, the system evolves in steps. In each step, one agent selected uniformly at random adopts with some probability {$\alpha$} the superior opinion, and with probability 1 - {$\alpha$} it follows an underlying update rule to revise its opinion on the basis of those held by its neighbors. We analyze the convergence of the resulting process under two wellknown update rules, namely majority and voter. The framework we propose exhibits a rich structure, with a nonobvious interplay between topology and underlying update rule. For example, for the voter rule we show that the speed of convergence bears no significant dependence on the underlying topology, whereas the picture changes completely under the majority rule, where network density negatively affects convergence. We believe that the model we propose is at the same time simple, rich, and modular, affording mathematical characterization of the interplay between bias, underlying opinion dynamics, and social structure in a unified setting.},
  file = {/home/aleksandar/Zotero/storage/5BGRV5U3/Anagnostopoulos et al. - 2020 - Biased Opinion Dynamics When the Devil is in the .pdf},
  isbn = {978-0-9992411-6-5},
  language = {en}
}

@article{AnalyzingComputationalModels,
  title = {Analyzing {{Computational Models}}},
  doi = {10.1111/ajps.12364},
  abstract = {{$<$}div class="abstract-group"{$>$}    {$<$}section class="article-section article-section\_\_abstract" lang="en" data-lang="en" id="section-1-en"{$>$}       {$<$}h3 class="article-section\_\_header main abstractlang\_en main"{$>$}Abstract{$<$}/h3{$>$}       {$<$}div class="article-section\_\_content en main"{$>$}                              {$<$}p{$>$}Computational models have been underutilized as tools for formal theory development,             closing off theoretical analysis of complex substantive scenarios that they would             well serve. I argue that this occurs for two reasons, and provide resolutions for             each. First, computational models generally do not employ the language or modes of             analysis common to game-theoretic models, the status quo in the literature. I detail             the types of insights typically derived from game-theoretic models and discuss analogues             in computational modeling. Second, there are not widely established procedures for             analysis of deductive computational models. I present a regularized method for deriving             comparative statics from computational models that provides insights comparable to             those arising from game-theoretic analyses. It also serves as a framework for building             theoretically tractable computational models. Together, these contributions should             enhance communication between models of social science and open up the tool kit of             deductive computational modeling for theory building to a broader audience.          {$<$}/p{$>$}},
  journal = {American Journal of Political Science}
}

@article{AnalyzingComputationalModelsa,
  title = {Analyzing {{Computational Models}}},
  doi = {10.1111/ajps.12364},
  abstract = {{$<$}div class="abstract-group"{$>$}    {$<$}section class="article-section article-section\_\_abstract" lang="en" data-lang="en" id="section-1-en"{$>$}       {$<$}h3 class="article-section\_\_header main abstractlang\_en main"{$>$}Abstract{$<$}/h3{$>$}       {$<$}div class="article-section\_\_content en main"{$>$}                              {$<$}p{$>$}Computational models have been underutilized as tools for formal theory development,             closing off theoretical analysis of complex substantive scenarios that they would             well serve. I argue that this occurs for two reasons, and provide resolutions for             each. First, computational models generally do not employ the language or modes of             analysis common to game-theoretic models, the status quo in the literature. I detail             the types of insights typically derived from game-theoretic models and discuss analogues             in computational modeling. Second, there are not widely established procedures for             analysis of deductive computational models. I present a regularized method for deriving             comparative statics from computational models that provides insights comparable to             those arising from game-theoretic analyses. It also serves as a framework for building             theoretically tractable computational models. Together, these contributions should             enhance communication between models of social science and open up the tool kit of             deductive computational modeling for theory building to a broader audience.          {$<$}/p{$>$}},
  journal = {American Journal of Political Science}
}

@article{andreevUnbearableLightnessMembership2009,
  title = {The Unbearable Lightness of Membership: {{Bulgaria}} and {{Romania}} after the 2007 {{EU}} Accession},
  shorttitle = {The Unbearable Lightness of Membership},
  author = {Andreev, Svetlozar A.},
  year = {2009},
  month = sep,
  volume = {42},
  pages = {375--393},
  doi = {10.1016/j.postcomstud.2009.07.001},
  journal = {Communist and Post-Communist Studies},
  language = {en},
  number = {3}
}

@article{anneGraphEstimationGaussianb,
  ids = {anneGraphEstimationGaussian,anneGraphEstimationGaussiana},
  title = {Graph Estimation for {{Gaussian}} Data Zero-Inflated by Double Truncation. ({{arXiv}}:1911.07694v1 [Math.{{ST}}])},
  author = {Anne, G{\'e}gout-Petit and Aur{\'e}lie, Gueudin-Muller and Cl{\'e}mence, Karmann},
  doi = {arXiv:1911.07694v1},
  abstract = {We consider the problem of graph estimation in a zero-inflated Gaussian model. In this model, zero-inflation is obtained by double truncation (right and left) of a Gaussian vector. The goal is to recover the latent graph structure of the Gaussian vector with observations of the zero-inflated truncated vector. We propose a two step estimation procedure. The first step consists in estimating each term of the covariance matrix by maximising the corresponding bivariate marginal log-likelihood of the truncated vector. The second one uses the graphical lasso procedure to estimate the precision matrix sparsity, which encodes the graph structure. We then state some theoretical convergence results about the convergence rate of the covariance matrix and precision matrix estimators. These results allow us to establish consistency of our procedure with respect to graph structure recovery. We also present some simulation studies to corroborate the efficiency of our procedure.},
  journal = {arXiv Statistics Theory}
}

@article{anselinLocalIndicatorsSpatial1995,
  title = {Local {{Indicators}} of {{Spatial Association}} - {{LISA}}},
  author = {Anselin, Luc},
  year = {1995},
  volume = {27},
  pages = {93--115},
  doi = {10.1111/j.1538-4632.1995.tb00338.x},
  journal = {Geographical Analysis},
  language = {en},
  number = {2}
}

@book{anselinSpatialEconometricsMethods2010,
  title = {Spatial Econometrics: {{Methods}} and Models},
  shorttitle = {Spatial Econometrics},
  author = {Anselin, Luc},
  year = {2010},
  publisher = {{Kluwer Academic}},
  address = {{Boston}},
  annotation = {OCLC: 854798713},
  isbn = {978-90-481-8311-1},
  language = {English}
}

@article{ansolabehereStrengthIssuesUsing2008,
  title = {The Strength of Issues: {{Using}} Multiple Measures to Gauge Preference Stability, Ideological Constraint, and Issue Voting},
  shorttitle = {The Strength of Issues},
  author = {Ansolabehere, Stephen and Rodden, Jonathan and Snyder, James M.},
  year = {2008},
  volume = {102},
  pages = {215--232},
  publisher = {{Cambridge University Press}},
  journal = {American Political Science Review},
  number = {2}
}

@article{anticParliamentaryElectionCroatia2008,
  title = {The Parliamentary Election in {{Croatia}}, {{November}} 2007},
  author = {Anti{\'c}, Miljenko and Grui{\v c}i{\'c}, Maja Dodi{\'c}},
  year = {2008},
  month = dec,
  volume = {27},
  pages = {752--755},
  issn = {02613794},
  doi = {10.1016/j.electstud.2008.04.015},
  journal = {Electoral Studies},
  language = {en},
  number = {4}
}

@article{anticParliamentaryElectionsCroatia2012,
  title = {The Parliamentary Elections in {{Croatia}}, {{December}} 2011},
  author = {Anti{\'c}, Miljenko},
  year = {2012},
  month = sep,
  volume = {31},
  pages = {636--639},
  issn = {02613794},
  doi = {10.1016/j.electstud.2012.04.004},
  journal = {Electoral Studies},
  language = {en},
  number = {3}
}

@article{antinyanSocialStatusCompetition,
  title = {Social Status Competition and the Impact of Income Inequality in Evolving Social Networks: {{An}} Agent-Based Model},
  author = {Antinyan, Armenak and Horvath, Gergely and Jia, Mofei},
  doi = {S2214804318301216},
  abstract = {{$<$}p{$>$}Publication date: Available online 2 January 2019{$<$}/p{$><$}p{$>$}\textbf{Source:} Journal of Behavioral and Experimental Economics{$<$}/p{$><$}p{$>$}Author(s): Armenak Antinyan, Gergely Horvath, Mofei Jia{$<$}/p{$><$}h5{$>$}Abstract{$<$}/h5{$><$}div{$><$}p{$>$}In this paper, we consider conspicuous consumption in a model in which individuals compare themselves to their social network neighbors in terms of the amount of a status good purchased. Individuals are heterogeneous with respect to income and can change their network links based on utility considerations. We study the impact of income inequality and income redistribution on status competition and individual welfare. We find that individuals with similar income levels tend to be connected to each other in the social network emerging in the long run. Under these circumstances, the income redistribution does not significantly affect the income share spent on the status good and the relative status of individuals. In a relatively equal society, individuals with below median income levels are better off in terms of welfare, everybody else are worse off. The aggregate effect of income redistribution on welfare is negative.{$<$}/p{$><$}/div{$>$}},
  journal = {Journal of Behavioral and Experimental Economics}
}

@article{antonicCleavagesSerbiaConsolidation2007,
  title = {Cleavages in {{Serbia}} and Consolidation of Democracy},
  author = {Antoni{\'c}, Slobodan},
  year = {2007},
  volume = {41},
  pages = {21--55},
  issn = {0085-6320},
  doi = {10.5937/socpreg0701021A},
  journal = {Sociolo\v{s}ki pregled},
  language = {en},
  number = {1}
}

@article{antonicElectoralVolatilitySerbia2005,
  title = {The Electoral Volatility in {{Serbia}}: {{Comparison}} and Explanation},
  shorttitle = {The Electoral Volatility in {{Serbia}}},
  author = {Antoni{\'c}, Slobodan},
  year = {2005},
  volume = {39},
  pages = {229--250},
  issn = {0085-6320},
  doi = {10.5937/socpreg0503229A},
  journal = {Sociolo\v{s}ki pregled},
  language = {en},
  number = {3}
}

@book{apaPublicationManualAmerican2010,
  title = {Publication Manual of the {{American Psychological Association}}},
  editor = {APA},
  year = {2010},
  edition = {6th ed},
  publisher = {{American Psychological Association}},
  address = {{Washington, DC}},
  isbn = {978-1-4338-0559-2 978-1-4338-0561-5 978-1-4338-0562-2},
  lccn = {BF76.7 .P83 2010}
}

@article{arangoHateSpeechDetection2020,
  title = {Hate Speech Detection Is Not as Easy as You May Think: {{A}} Closer Look at Model Validation (Extended Version)},
  shorttitle = {Hate Speech Detection Is Not as Easy as You May Think},
  author = {Arango, Aym{\'e} and P{\'e}rez, Jorge and Poblete, Barbara},
  year = {2020},
  month = jun,
  pages = {101584},
  issn = {0306-4379},
  doi = {10.1016/j.is.2020.101584},
  abstract = {Hate speech is an important problem that is seriously affecting the dynamics and usefulness of online social communities. Large scale social platforms are currently investing important resources into automatically detecting and classifying hateful content, without much success. On the other hand, the results reported by state-of-the-art systems indicate that supervised approaches achieve almost perfect performance but only within specific datasets, most of them in English language. In this work, we analyze this apparent contradiction between existing literature and actual applications. We study closely the experimental methodology used in prior work and their generalizability to other datasets. Our findings evidence methodological issues, as well as an important dataset bias. As a consequence, performance claims of the current state-of-the-art have become significantly overestimated. The problems that we have found are mostly related to data overfitting and sampling issues. We discuss the implications for current research and re-conduct experiments to give a more accurate picture of the current state-of-the art methods. Moreover, we design some baseline approaches to perform cross-lingual experiments, using English and Spanish datasets.},
  file = {/home/aleksandar/Zotero/storage/UM2GN7Q8/S0306437920300715.html},
  journal = {Information Systems},
  language = {en}
}

@article{arefMultilevelStructuralEvaluation2020,
  title = {Multilevel {{Structural Evaluation}} of {{Signed Directed Social Networks}} Based on {{Balance Theory}}},
  author = {Aref, Samin and Dinh, Ly and Rezapour, Rezvaneh and Diesner, Jana},
  year = {2020},
  month = jul,
  abstract = {Balance theory explains the forces behind the structure of social systems, which are commonly modeled as static undirected signed networks. We expand this modeling approach to incorporate directionality of edges, and consider three levels of analysis: triads, subgroups, and the whole network. For triad-level balance, we operationalize a new measure by utilizing semicycles that satisfy the condition of transitivity. For subgroup-level balance, we propose measures of cohesiveness (intra-group solidarity) and divisiveness (inter-group antagonism) to capture balance within and among subgroups of the network using the most fitting partition of nodes into two groups. For network-level balance, we re-purpose the normalized line index to incorporate directionality, and provide the proportion of edges whose position suits balance. Through extensive computational analysis, we quantify and analyze patterns of social structure in triads, subgroups, and the whole network across a range of social settings from college students and Wikipedia editors to philosophers and Bitcoin traders. We then apply our multilevel framework of analysis to examine balance in temporal and multilayer networks, which demonstrates the generalizability of our approach to evaluating balance, and leads to new observations on balance with respect to time and layer dimensions. Our complementary findings on a variety of social networks highlight the need to evaluate balance at different levels. We propose a comprehensive yet parsimonious approach to address this need.},
  archivePrefix = {arXiv},
  eprint = {2005.09925},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Dropbox/Zotero/Aref et al/Aref et al_2020_Multilevel Structural Evaluation of Signed Directed Social Networks based on.pdf;/home/aleksandar/Zotero/storage/Q34UNBJH/2005.html},
  journal = {arXiv:2005.09925 [physics]},
  primaryClass = {physics}
}

@article{armalyRoleAffectiveOrientationsundefined/ed,
  title = {The Role of Affective Orientations in Promoting Perceived Polarization},
  author = {Armaly, Miles T. and Enders, Adam M.},
  year = {undefined/ed},
  pages = {1--12},
  publisher = {{Cambridge University Press}},
  issn = {2049-8470, 2049-8489},
  doi = {10.1017/psrm.2020.24},
  abstract = {Recent work on political divisions in the mass public has identified several manifestations of polarization linked to different types of attitudes, orientations, and behaviors. Of these, affective polarization and perceived polarization have attracted increasing attention, though we still know fairly little of the links between these variants of polarization. In this paper, we examine the association between affective and perceived polarization, with an aim toward disentangling any potential causal relationship between the two processes. Using two sets of nationally representative panel data from 1992 to 1996 and 2008 to 2009, we find evidence that affective polarization causes perceived polarization, and that perceived polarization is not related to future affective polarization. Stratifying the models by level of political information, we find that the strength and statistical significance of the relationships between past and future values of affective and perceived polarization are conditional on political sophistication: more sophisticated individuals exhibit stronger relationships.},
  file = {/home/aleksandar/Zotero/storage/V9BRG9GJ/8DC909776671F0791C5B6DDE407F5D1E.html},
  journal = {Political Science Research and Methods},
  language = {en}
}

@book{armstrongAnalyzingSpatialModels2014a,
  title = {Analyzing {{Spatial Models}} of {{Choice}} and {{Judgment}} with {{R}}.},
  author = {Armstrong, II},
  year = {2014},
  publisher = {{Chapman and Hall/CRC}},
  annotation = {OCLC: 872618556},
  isbn = {978-1-306-50163-7 978-1-4665-1715-8 978-1-4665-1716-5},
  language = {English}
}

@article{arnesenConditionalLegitimacyHow2019,
  title = {Conditional Legitimacy: {{How}} Turnout, Majority Size, and Outcome Affect Perceptions of Legitimacy in {{European Union}} Membership Referendums},
  shorttitle = {Conditional Legitimacy},
  author = {Arnesen, Sveinung and Broderstad, Troy S and Johannesson, Mikael P and Linde, Jonas},
  year = {2019},
  month = feb,
  pages = {146511651882016},
  issn = {1465-1165, 1741-2757},
  doi = {10.1177/1465116518820163},
  journal = {European Union Politics},
  language = {en}
}

@article{arroyoOverlappingCommunityDetection2020,
  title = {Overlapping Community Detection in Networks via Sparse Spectral Decomposition},
  author = {Arroyo, Jes{\'u}s and Levina, Elizaveta},
  year = {2020},
  month = sep,
  abstract = {We consider the problem of estimating overlapping community memberships in a network, where each node can belong to multiple communities. More than a few communities per node are difficult to both estimate and interpret, so we focus on sparse node membership vectors. Our algorithm is based on sparse principal subspace estimation with iterative thresholding. The method is computationally efficient, with a computational cost equivalent to estimating the leading eigenvectors of the adjacency matrix, and does not require an additional clustering step, unlike spectral clustering methods. We show that a fixed point of the algorithm corresponds to correct node memberships under a version of the stochastic block model. The methods are evaluated empirically on simulated and real-world networks, showing good statistical performance and computational efficiency.},
  archivePrefix = {arXiv},
  eprint = {2009.10641},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Arroyo_Levina/Arroyo_Levina_2020_Overlapping community detection in networks via sparse spectral decomposition.pdf;/home/aleksandar/Zotero/storage/WIIJPFFP/2009.html},
  journal = {arXiv:2009.10641 [cs, stat]},
  primaryClass = {cs, stat}
}

@article{artnerShapePartialCorrelation2020,
  title = {The Shape of Partial Correlation Matrices},
  author = {Artner, Richard and Wellingerhof, Paul P. and Lafit, Ginette and Loossens, Tim and Vanpaemel, Wolf and Tuerlinckx, Francis},
  year = {2020},
  month = sep,
  volume = {0},
  pages = {1--18},
  publisher = {{Taylor \& Francis}},
  issn = {0361-0926},
  doi = {10.1080/03610926.2020.1811338},
  abstract = {The correlational structure of a set of variables is often conveniently described by the pairwise partial correlations as they contain the same information as the Pearson correlations with the advantage of straightforward identifications of conditional linear independence. For mathematical convenience, multiple matrix representations of the pairwise partial correlations exist in the literature but their properties have not been investigated thoroughly. In this paper, we derive necessary and sufficient conditions for the eigenvalues of differently defined partial correlation matrices so that the correlation structure is a valid one. Equipped with these conditions, we will then emphasize the intricacies of algorithmic generations of correlation structures via partial correlation matrices. Furthermore, we examine the space of valid partial correlation structures and juxtapose it with the space of valid Pearson correlation structures. As these spaces turn out to be equal in volume for every dimension and equivalent with respect to rotation, a simple formula allows the creation of valid partial correlation matrices by the use of current algorithms for the generation and approximation of correlation matrices. Lastly, we derive simple conditions on the partial correlations for frequently assumed sparse structures.},
  annotation = {\_eprint: https://doi.org/10.1080/03610926.2020.1811338},
  file = {/home/aleksandar/Zotero/storage/KQIBQZ6W/03610926.2020.html},
  journal = {Communications in Statistics - Theory and Methods},
  number = {0}
}

@article{arugueteTrustfulVotersTrustworthy2020,
  title = {Trustful {{Voters}}, {{Trustworthy Politicians}}: {{A Survey Experiment}} on the {{Influence}} of {{Social Media}} in {{Politics}} *},
  shorttitle = {Trustful {{Voters}}, {{Trustworthy Politicians}}},
  author = {Aruguete, Natalia and Calvo, Ernesto and Scartascini, Carlos and Ventura, Tiago},
  year = {2020},
  publisher = {{Unpublished}},
  doi = {10.13140/RG.2.2.26137.65123},
  abstract = {Recent increases in uncivil dialogue, political polarization, and fake news in social media raise questions about the relationship between negative online messages and the decline in political trust. We implement a trust game in a survey experiment with 4,800 respondents in Brazil and Mexico. Our design models the effect of social media on trust and trustworthiness. Survey respondents alternate as agents (politicians) and principals (voters), with rewards contingent on their preferred ``candidate'' winning the election. We measure the extent to which voters place their trust in others and are themselves trustworthy, that is, willing to honor requests that may not benefit them. Results provide robust support for a negative effect of uncivil partisan discourse on trust behavior and null results on trustworthiness.},
  file = {/home/aleksandar/Zotero/storage/XJ8SU4JJ/Aruguete et al. - 2020 - Trustful Voters, Trustworthy Politicians A Survey.pdf},
  language = {en}
}

@article{ascherStabilityCommunistElectorates1975,
  title = {The Stability of Communist Electorates: {{Evidence}} from a Longitudinal Analysis of {{French}} and {{Italian}} Aggregate {{Data}}},
  shorttitle = {The {{Stability}} of {{Communist Electorates}}},
  author = {Ascher, William and Tarrow, Sidney},
  year = {1975},
  month = aug,
  volume = {19},
  pages = {475},
  issn = {00925853},
  doi = {10.2307/2110540},
  journal = {American Journal of Political Science},
  number = {3}
}

@techreport{ashokkumarCensoringPoliticalOpposition2020,
  title = {Censoring {{Political Opposition Online}}: {{Who Does}} It and {{Why}}},
  shorttitle = {Censoring {{Political Opposition Online}}},
  author = {Ashokkumar, Ashwini and Talaifar, Sanaz and Fraser, William T. and Landabur, Rodrigo and Burhmester, Michael and G{\'o}mez, {\'A}ngel and Paredes, Borja and Swann, William B.},
  year = {2020},
  month = jul,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/r9c5z},
  abstract = {As ordinary citizens increasingly moderate online forums, blogs, and their own social media feeds, a new type of censoring has emerged wherein people selectively remove opposing political viewpoints from online contexts. In three studies of behavior on putative online forums, supporters of a political cause (e.g., abortion or gun rights) preferentially censored comments that opposed their cause. The tendency to selectively censor cause-incongruent online content was amplified among people whose cause-related beliefs were deeply rooted in or ``fused with'' their identities. Moreover, six additional identity-related measures also amplified the selective censoring effect. Finally, selective censoring emerged even when opposing comments were inoffensive and courteous. We suggest that because online censorship enacted by moderators can skew online content consumed by millions of users, it can systematically disrupt democratic dialogue and subvert social harmony.},
  file = {/home/aleksandar/Zotero/storage/4CPRWMA3/Ashokkumar et al. - 2020 - Censoring Political Opposition Online Who Does it.pdf},
  language = {en},
  type = {Preprint}
}

@article{asimTrustModelAnalysis2019,
  title = {A Trust Model for Analysis of Trust, Influence and Their Relationship in Social Network Communities},
  author = {Asim, Yousra and Malik, Ahmad Kamran and Raza, Basit and Shahid, Ahmad Raza},
  year = {2019},
  month = mar,
  volume = {36},
  pages = {94--116},
  issn = {0736-5853},
  doi = {10.1016/j.tele.2018.11.008},
  abstract = {Influential nodes are capable of influencing the Social Network (SN) structure and functions. Influential nodes are not pre-defined and need to be identified to better understand and control the network. Trust of the nodes can be an important indicator of their influence and trusted nodes can also affect other nodes. However, analysis of trust and influence relationship in social network communities needs investigation. This study proposes a SNTrust model to find the trust of nodes in a network using a local and global trust and also investigates trust, influence and their relationship in SN communities. Different SN-based influence evaluation approaches named K-core, closeness centrality, eigenvector centrality, and page rank is used to find influential nodes. We have explored the trust and influence of nodes in their communities as well as in the network. Different standard datasets such as Consulting Company dataset, Freeman EIES dataset, Blogcatalogue dataset, and Facebook groups dataset are used for experimentation and Pearson's correlation and level of significance (p-value) are used for results evaluation. We found a positive linear correlation between the local trust of a node and its influence. It is found that the nodes which are trusted in the network are highly trusted in their communities. There is a strong linear relationship between the influence of a node in the network and community. Furthermore, it is also observed that nodes that are close to each other in a community have high trust among them. The results show that the proposed SNTrust model performed better in finding trust, influence and their correlation.},
  file = {/home/aleksandar/Dropbox/Zotero/Asim et al/Asim et al_2019_A trust model for analysis of trust, influence and their relationship in social.pdf;/home/aleksandar/Zotero/storage/VHTUSIT6/S0736585318308955.html},
  journal = {Telematics and Informatics},
  language = {en}
}

@article{asparouhovAdvancesBayesianModel2019,
  title = {Advances in {{Bayesian Model Fit Evaluation}} for {{Structural Equation Models}}},
  author = {Asparouhov, Tihomir and Muthen, Bengt},
  year = {2019},
  pages = {36},
  abstract = {In this article we discuss the Posterior Predictive P-value (PPP) method in the presence of missing data, the Bayesian adaptation of the approximate fit indices RMSEA, CFI and TLI, as well as the Bayesian adaptation of the Wald test for nested models. Simulation studies are presented. We also illustrate how these new methods can be used to build BSEM models.},
  language = {en}
}

@inproceedings{assenmacherTwoPhaseFrameworkDetecting2020,
  title = {A {{Two}}-{{Phase Framework}} for {{Detecting Manipulation Campaigns}} in {{Social Media}}},
  booktitle = {Social {{Computing}} and {{Social Media}}. {{Design}}, {{Ethics}}, {{User Behavior}}, and {{Social Network Analysis}}},
  author = {Assenmacher, Dennis and Clever, Lena and Pohl, Janina Susanne and Trautmann, Heike and Grimme, Christian},
  editor = {Meiselwitz, Gabriele},
  year = {2020},
  pages = {201--214},
  publisher = {{Springer International Publishing}},
  address = {{Cham}},
  doi = {10.1007/978-3-030-49570-1_14},
  abstract = {The identification of coordinated campaigns within Social Media is a complex task that is often hindered by missing labels and large amounts of data that have to be processed. We propose a new two-phase framework that uses unsupervised stream clustering for detecting suspicious trends over time in a first step. Afterwards, traditional offline analyses are applied to distinguish between normal trend evolution and malicious manipulation attempts. We demonstrate the applicability of our framework in the context of the final days of the Brexit in 2019/2020.},
  file = {/home/aleksandar/Dropbox/Zotero/Assenmacher et al/Assenmacher et al_2020_A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media.pdf},
  isbn = {978-3-030-49570-1},
  language = {en},
  series = {Lecture {{Notes}} in {{Computer Science}}}
}

@article{asunkaElectoralFraudViolence,
  title = {Electoral {{Fraud}} or {{Violence}}: {{The Effect}} of {{Observers}} on {{Party Manipulation Strategies}}},
  author = {Asunka, Joseph and Brierley, Sarah and Golden, Miriam and Kramon, Eric and Ofosu, George},
  doi = {10.1017/S0007123416000491},
  abstract = {{$<$}p{$>$}This article reports on the effects of domestic election observers on electoral fraud and violence. Using an experimental research design and polling station data on fraud and violence during Ghana's 2012 elections, it shows that observers reduced fraud and violence at the polling stations which they monitored. It is argued that local electoral competition shapes party activists' response to observers. As expected, in single-party dominant areas, parties used their local political networks to relocate fraud to polling stations without an election observer, and, in contrast, party activists relocated violence to stations without observers in competitive areas \textendash{} a response that requires less local organizational capacity. This highlights how local party organization and electoral incentives can shape the manipulative electoral strategies employed by parties in democratic elections.{$<$}/p{$>$}},
  journal = {British Journal of Political Science}
}

@misc{AsymptoticResolutionBounds,
  title = {Asymptotic Resolution Bounds of Generalized Modularity and Multi-Scale Community Detection - {{ScienceDirect}}},
  file = {/home/aleksandar/Dropbox/Zotero/undefined/Asymptotic resolution bounds of generalized modularity and multi-scale.pdf},
  howpublished = {https://www.sciencedirect.com/science/article/pii/S0020025520302632}
}

@article{atchadeQuasiBayesianEstimationLarge,
  title = {Quasi-{{Bayesian}} Estimation of Large {{Gaussian}} Graphical Models},
  author = {Atchad{\'e}, Yves F.},
  doi = {10.1016/j.jmva.2019.03.005},
  abstract = {{$<$}p{$>$}This paper deals with the Bayesian estimation of large precision matrices in Gaussian graphical models. We develop a quasi-Bayesian implementation of the neighborhood selection method of Meinshausen and B\"uhlmann (2016). The method produces a product-form quasi-posterior distribution that can be efficiently explored by parallel computing. Under some restrictions on the true precision matrix, we show that the quasi-posterior distribution contracts in the spectral norm at the rate of {$<$}math{$>$}O\{s{$\star$}ln(p)/n\}{$<$}/math{$>$}, where {$<$}math{$>$}p{$<$}/math{$>$} is the number of nodes in the graph, {$<$}math{$>$}n{$<$}/math{$>$} the sample size, and {$<$}math{$>$}s{$\star<$}/math{$>$} is the maximum degree of the undirected graph defined by the true precision matrix. We develop a Markov Chain Monte Carlo algorithm for approximate computations, following an approach from Atchad\'e (2019). We illustrate the methodology using real and simulated data examples.{$<$}/p{$>$}},
  journal = {Journal of Multivariate Analysis}
}

@article{atchadeQuasiBayesianEstimationLargea,
  title = {Quasi-{{Bayesian}} Estimation of Large {{Gaussian}} Graphical Models},
  author = {Atchad{\'e}, Yves F.},
  doi = {10.1016/j.jmva.2019.03.005},
  abstract = {{$<$}p{$>$}This paper deals with the Bayesian estimation of large precision matrices in Gaussian graphical models. We develop a quasi-Bayesian implementation of the neighborhood selection method of Meinshausen and B\"uhlmann (2016). The method produces a product-form quasi-posterior distribution that can be efficiently explored by parallel computing. Under some restrictions on the true precision matrix, we show that the quasi-posterior distribution contracts in the spectral norm at the rate of {$<$}math{$>$}O\{s{$\star$}ln(p)/n\}{$<$}/math{$>$}, where {$<$}math{$>$}p{$<$}/math{$>$} is the number of nodes in the graph, {$<$}math{$>$}n{$<$}/math{$>$} the sample size, and {$<$}math{$>$}s{$\star<$}/math{$>$} is the maximum degree of the undirected graph defined by the true precision matrix. We develop a Markov Chain Monte Carlo algorithm for approximate computations, following an approach from Atchad\'e (2019). We illustrate the methodology using real and simulated data examples.{$<$}/p{$>$}},
  journal = {Journal of Multivariate Analysis}
}

@book{atkesonOxfordHandbookPolling2018,
  title = {The {{Oxford}} Handbook of Polling and Survey Methods},
  editor = {Atkeson, Lonna Rae and Alvarez, R. Michael},
  year = {2018},
  publisher = {{Oxford University Press}},
  address = {{New York, NY}},
  isbn = {978-0-19-021329-9},
  lccn = {HM1236 .O945 2018}
}

@article{ayllonKeepingModellingNotebooks2021,
  title = {Keeping Modelling Notebooks with {{TRACE}}: {{Good}} for You and Good for Environmental Research and Management Support},
  shorttitle = {Keeping Modelling Notebooks with {{TRACE}}},
  author = {Ayll{\'o}n, Daniel and Railsback, Steven F. and Gallagher, Cara and Augusiak, Jacqueline and Baveco, Hans and Berger, Uta and Charles, Sandrine and Martin, Romina and Focks, Andreas and Galic, Nika and Liu, Chun and {van Loon}, E. Emiel and {Nabe-Nielsen}, Jacob and Piou, Cyril and Polhill, J. Gareth and Preuss, Thomas G. and Radchuk, Viktoriia and Schmolke, Amelie and {Stadnicka-Michalak}, Julita and Thorbek, Pernille and Grimm, Volker},
  year = {2021},
  month = feb,
  volume = {136},
  pages = {104932},
  issn = {1364-8152},
  doi = {10.1016/j.envsoft.2020.104932},
  abstract = {The acceptance and usefulness of simulation models are often limited by the efficiency, transparency, reproducibility, and reliability of the modelling process. We address these issues by suggesting that modellers (1) ``trace'' the iterative modelling process by keeping a modelling notebook corresponding to the laboratory notebooks used by empirical researchers, (2) use a standardized notebook structure and terminology based on the existing TRACE documentation framework, and (3) use their notebooks to compile TRACE documents that supplement publications and reports. These practices have benefits for model developers, users, and stakeholders: improved and efficient model design, analysis, testing, and application; increased model acceptance and reuse; and replicability and reproducibility of the model and the simulation experiments. Using TRACE terminology and structure in modelling notebooks facilitates production of TRACE documents. We explain the rationale of TRACE, provide example TRACE documents, and suggest strategies for keeping ``TRACE Modelling Notebooks.''},
  file = {/home/aleksandar/Zotero/storage/NVIU776I/S1364815220309890.html},
  journal = {Environmental Modelling \& Software},
  keywords = {Environmental modelling,Model documentation,Modelling cycle,Reproducible research,Scientific communication,Standards},
  language = {en}
}

@article{babeanuRandomMatrixPerspective2020,
  title = {A Random Matrix Perspective of Cultural Structure: Groups or Redundancies?},
  shorttitle = {A Random Matrix Perspective of Cultural Structure},
  author = {B{\u a}beanu, Alexandru Ionuț},
  year = {2020},
  month = nov,
  issn = {2632-072X},
  doi = {10.1088/2632-072X/abc859},
  file = {/home/aleksandar/Zotero/storage/SE3MPEAJ/Băbeanu - 2020 - A random matrix perspective of cultural structure.pdf},
  journal = {Journal of Physics: Complexity},
  language = {en}
}

@article{babveyContentAwareGalaxiesDigital2020,
  title = {Content-{{Aware Galaxies}}: {{Digital Fingerprints}} of {{Discussions}} on {{Social Media}}},
  shorttitle = {Content-{{Aware Galaxies}}},
  author = {Babvey, P. and Borrelli, D. and Lipizzi, C. and {Ramirez-Marquez}, J. E.},
  year = {2020},
  pages = {1--14},
  issn = {2329-924X},
  doi = {10.1109/TCSS.2020.3024762},
  abstract = {The emergence of social media has facilitated new ways of communication and social engagement. Political elites and public figures use social media to inform and mobilize users. Discussions appearing around these tweets reflect valuable information from the communities, their interests, and concerns. The majority of the studies on conversational dynamics on social media use the network between users to track the flow of information and impact. In this study, a different approach is introduced in which discussion threads as the network between tweets are considered as the main components of the analysis. Based on this approach, a novel framework is proposed to provide a high-level overview of a Twitter stream. The metric energy is introduced to quantify user engagement in discussions initiated by each tweet and to study the patterns of user-participation overtime. To mine the content of the tweets, some recently developed text analysis methods are integrated into our model to extract the topic of the tweets, the sentiment of the tweets, the stance of tweets toward a controversial topic, and the coherency between the tweet-reply pairs. Three different data sets from politics, healthcare, and sport are collected to be used as case studies. The proposed framework provides a better understanding of how opinions form around a tweet, how different topics to bond together and make the whole discussions, for which topics discussions are more coherent, and which users are able to initiate a cross cutting and coherent conversation over social media.},
  file = {/home/aleksandar/Zotero/storage/DF3PEMME/9210824.html},
  journal = {IEEE Transactions on Computational Social Systems},
  keywords = {Analytical models,Conversational dynamics,Measurement,Message systems,sentiment analysis,social network analysis,stance classification,Tagging,text analytics,topic extraction,topic-aware networks,Twitter,visual summarization.,Visualization}
}

@incollection{bacharachZerosumGames1989,
  title = {Zero-Sum Games},
  booktitle = {Game Theory},
  author = {Bacharach, Michael},
  editor = {Eatwell, John and Milgate, Murray and Newman, Peter},
  year = {1989},
  pages = {253--257},
  publisher = {{Palgrave Macmillan}},
  address = {{London}},
  doi = {10.1007/978-1-349-20181-5_31},
  isbn = {978-0-333-49537-7 978-1-349-20181-5},
  language = {en}
}

@article{badhamNetworkStructureInfluence2021,
  title = {Network Structure Influence on Simulated Network Interventions for Behaviour Change},
  author = {Badham, Jennifer and Kee, Frank and Hunter, Ruth F.},
  year = {2021},
  month = jan,
  volume = {64},
  pages = {55--62},
  issn = {0378-8733},
  doi = {10.1016/j.socnet.2020.08.003},
  abstract = {We simulated diffusion of behaviour change over fifteen real-world networks with seven network interventions under both simple and complex contagion. We found that structural network properties affect both the diffusion outcome and the relative effectiveness of the different interventions, with confounding effects that were inconsistent with results expected from mathematical analysis. These results suggest that comprehensive studies are needed to identify the effects of structural properties on diffusion in real-world networks. Further, researchers attempting to identify the effect of individual properties must measure a range of properties to avoid incorrect attribution.},
  file = {/home/aleksandar/Zotero/storage/CL92IQYS/Badham et al_2021_Network structure influence on simulated network interventions for behaviour.pdf;/home/aleksandar/Zotero/storage/NPL29NTU/S037887332030071X.html},
  journal = {Social Networks},
  language = {en}
}

@inproceedings{bagenholmWhyArePostcommunist2013,
  title = {Why Are the Post-Communist Party Systems Not Stabilizing?},
  booktitle = {{{ECPR Joint Sessions}} ({{Workshop}} 31)},
  author = {B{\aa}genholm, Andreas and Hein{\"o}, Andreas Johansson},
  year = {2013},
  address = {{Mainz}}
}

@article{bagherikalhorHeiderBalanceDisordered2020,
  title = {Heider {{Balance}} under {{Disordered Triadic Interactions}}},
  author = {Bagherikalhor, M. and Kargaran, A. and Shirazi, A. H. and Jafari, G. R.},
  year = {2020},
  month = nov,
  abstract = {The Heider balance addresses three-body interactions with the assumption that triads are equally important in the dynamics of the network. In many networks, the relations do not have the same strength so, triads are differently weighted. Now, the question is how social networks evolve to reduce the number of unbalanced triangles when they are weighted? Are the results foreseeable based on what we have already learned from the unweighted balance? To find the solution, we consider a fully connected network in which triads are assigned with different random weights. Weights are coming from Gaussian probability distribution with mean \$\textbackslash mu\$ and variance \$\textbackslash sigma\$. We study this system in two regimes : (\textbackslash RN\{1\}) the ratio of \$\textbackslash frac\{\textbackslash mu\}\{\textbackslash sigma\} \textbackslash ge 1 \$ corresponds to weak disorder (small variance) that triads' weight are approximately the same, (\textbackslash RN\{2\}) \$\textbackslash frac\{\textbackslash mu\}\{\textbackslash sigma\} {$<$} 1 \$ counts for strong disorder (big variance) and weights are remarkably diverse. Investigating the structural evolution of such a network is our intention. We see disorder plays a key role in determining the critical temperature of the system. Using the mean-field method to present an analytic solution for the system represents that the system undergoes a first-order phase transition. For weak disorder, our simulation results display the system reaches the global minimum as temperature decreases whereas for high disorder we manage to see a seudo-Kondo effect in triadic interactions. The Kondo effect explains the anomalous increase in electrical resistivity of metals due to magnetic impurities at low temperatures. Similar behavior is seen in the energy versus temperature in our work for the second regime and the system does not reach a global minimum.},
  archivePrefix = {arXiv},
  eprint = {2011.02651},
  eprinttype = {arxiv},
  file = {/home/aleksandar/Documents/Zotero/Bagherikalhor et al/Bagherikalhor et al_2020_Heider Balance under Disordered Triadic Interactions.pdf;/home/aleksandar/Zotero/storage/PS5JDCPH/2011.html},
  journal = {arXiv:2011.02651 [physics]},
  keywords = {Physics - Physics and Society},
  primaryClass = {physics}
}

@article{bagozziBayesianSplitPopulation2019,
  title = {A {{Bayesian Split Population Survival Model}} for {{Duration Data With Misclassified Failure Events}}},
  author = {Bagozzi, Benjamin E. and Joo, Minnie M. and Kim, Bomin and Mukherjee, Bumba},
  year = {2019},
  month = oct,
  volume = {27},
  pages = {415--434},
  issn = {1047-1987, 1476-4989},
  doi = {10.1017/pan.2019.6},
  abstract = {We develop a new Bayesian split population survival model for the analysis of survival data with misclassified event failures. Within political science survival data, right-censored survival cases are often erroneously misclassified as failure cases due to measurement error. Treating these cases as failure events within survival analyses will underestimate the duration of some events. This will bias coefficient estimates, especially in situations where such misclassification is associated with covariates of interest. Our split population survival estimator addresses this challenge by using a system of two equations to explicitly model the misclassification of failure events alongside a parametric survival process of interest. After deriving this model, we use Bayesian estimation via slice sampling to evaluate its performance with simulated data, and in several political science applications. We find that our proposed ``misclassified failure'' survival model allows researchers to accurately account for misclassified failure events within the contexts of civil war duration and democratic survival.},
  file = {/home/aleksandar/Zotero/storage/BUK948FY/3C00E441B1E9F6BA05993C4A827D094A.html},
  journal = {Political Analysis},
  language = {en},
  number = {4}
}

@article{bakarBayesianSpatialCategorical2019,
  title = {A {{Bayesian}} Spatial Categorical Model for Prediction to Overlapping Geographical Areas in Sample Surveys},
  author = {Bakar, K. Shuvo and Biddle, Nicholas and Kokic, Philip and Jin, Huidong},
  year = {2019},
  volume = {n/a},
  issn = {1467-985X},
  doi = {10.1111/rssa.12526},
  abstract = {Motivated by the Australian National University poll, we consider a situation where survey data have been collected from respondents for several categorical variables and a primary geographic classification, e.g. postcode. Here, a common and important problem is to obtain estimates for a second target geography that overlaps with the primary geography but has not been collected from the respondents. We examine this problem when areal level census information is available for both geographic classifications. Such a situation is challenging from a small area estimation perspective for several reasons: there is a misalignment between the census and survey information as well as the geographical classifications; the geographic areas are potentially small and so prediction can be difficult because of the sparse or spatially missing data issue; and there is the possibility of non-stationary spatial dependence. To address these problems we develop a Bayesian model using latent processes, underpinned by a non-stationary spatial basis that combines Moran's I and multiresolution basis functions with a small but representative set of knots. The study results based on simulated data demonstrate that the model can be highly effective and gives more accurate estimates for areas defined by the target geography than several existing models. The model also performs well for the Australian National University poll data to predict on a second geographic classification: statistical area level 2.},
  copyright = {\textcopyright{} 2019 Royal Statistical Society},
  journal = {Journal of the Royal Statistical Society: Series A (Statistics in Society)},
  language = {en},
  number = {n/a}
}

@article{bakkePatternsStabilityParty2005,
  title = {Patterns of Stability: Party Competition and Strategy in {{Central Europe}} since 1989},
  shorttitle = {Patterns of {{Stability}}},
  author = {Bakke, Elisabeth and Sitter, Nick},
  year = {2005},
  month = mar,
  volume = {11},
  pages = {243--263},
  issn = {1354-0688, 1460-3683},
  doi = {10.1177/1354068805049779},
  journal = {Party Politics},
  language = {en},
  number = {2}
}

@article{bakkTwoStepEstimationModels,
  title = {Two-{{Step Estimation}} of {{Models Between Latent Classes}} and {{External Variables}}},
  author = {Bakk, Zsuzsa and Kuha, Jouni},
  doi = {10.1007/s11336-017-9592-7},
  abstract = {{$<$}h3 class="a-plus-plus"{$>$}Abstract{$<$}/h3{$>$}                     {$<$}p class="a-plus-plus"{$>$}We consider models which combine latent class measurement models for categorical latent variables with structural regression models for the relationships between the latent classes and observed explanatory and response variables. We propose a two-step method of estimating such models. In its first step, the measurement model is estimated alone, and in the second step the parameters of this measurement model are held fixed when the structural model is estimated. Simulation studies and applied examples suggest that the two-step method is an attractive alternative to existing one-step and three-step methods. We derive estimated standard errors for the two-step estimates of the structural model which account for the uncertainty from both steps of the estimation, and show how the method can be implemented in existing software for latent variable modelling.{$<$}/p{$>$}},
  journal = {Psychometrika}
}

@article{bakkTwoStepEstimationModelsa,
  title = {Two-{{Step Estimation}} of {{Models Between Latent Classes}} and {{External Variables}}},
  author = {Bakk, Zsuzsa and Kuha, Jouni},
  doi = {10.1007/s11336-017-9592-7},
  abstract = {{$<$}h3 class="a-plus-plus"{$>$}Abstract{$<$}/h3{$>$}                     {$<$}p class="a-plus-plus"{$>$}We consider models which combine latent class measurement models for categorical latent variables with structural regression models for the relationships between the latent classes and observed explanatory and response variables. We propose a two-step method of estimating such models. In its first step, the measurement model is estimated alone, and in the second step the parameters of this measurement model are held fixed when the structural model is estimated. Simulation studies and applied examples suggest that the two-step method is an attractive alternative to existing one-step and three-step methods. We derive estimated standard errors for the two-step estimates of the structural model which account for the uncertainty from both steps of the estimation, and show how the method can be implemented in existing software for latent variable modelling.{$<$}/p{$>$}},
  journal = {Psychometrika}
}

@techreport{ballardIntegratedApproachTesting2018,
  title = {An Integrated Approach to Testing Dynamic, Multilevel Theory: {{Using}} Computational Models to Connect Theory, Model, and Data},
  shorttitle = {An Integrated Approach to Testing Dynamic, Multilevel Theory},
  author = {Ballard, Timothy and Palada, Hector and Griffin, Mark and Neal, Andrew},
  year = {2018},
  month = jul,
  institution = {{PsyArXiv}},
  doi = {10.31234/osf.io/3djt5},
  abstract = {Some of the most influential theories in organizational sciences explicitly describe a dynamic, multilevel process. Yet the inherent complexity of such theories makes them difficult to test. These theories often describe multiple sub-processes that interact reciprocally over time, at different levels of analysis, and over different time scales. Computational (i.e., mathematical) modeling is increasingly advocated as a method for developing and testing theories of this type. In organizational sciences however, efforts that have been made to test models empirically are often indirect. We argue that the full potential of computational modeling as a tool for testing dynamic, multilevel theory is yet to be realized. In this paper, we demonstrate an approach to testing dynamic, multilevel theory using computational modeling. The approach uses simulations to generate model predictions, and Bayesian parameter estimation to fit models to empirical data and to facilitate model comparisons. This approach enables a direct integration between theory, model, and data, that we believe enables a more rigorous test of theory.},
  language = {en},
  type = {Preprint}
}

@article{banerjeeBayesianInferenceHighdimensional,
  title = {Bayesian Inference in High-Dimensional Models},
  author = {Banerjee, Sayantan and Castillo, Ismael and Ghosal, Subhashis},
  pages = {34},
  abstract = {Models with dimension often more than the available sample size are now commonly used in various applications. A sensible inference is possible using a lower-dimensional structure. In regression problems with a large number of predictors, the model is often assumed to be sparse, with only a few predictors active. Interdependence between a large number of variables is succinctly described by a graphical model, where variables are represented by nodes on a graph and an edge between two nodes is used to indicate their conditional dependence given other variables. Many procedures for making inferences in the high-dimensional setting, typically using penalty functions to induce sparsity in the solution obtained by minimizing a loss function, were developed. Bayesian methods have been proposed for such problems more recently, where the prior takes care of the sparsity structure. These methods have the natural ability to also automatically quantify the uncertainty of the inference through the posterior distribution. Theoretical studies of Bayesian procedures in high-dimension have been carried out recently. Questions that arise are whether the posterior distribution contracts near the true value of the parameter at the minimax optimal rate, whether the correct lower-dimensional structure is discovered with high posterior probability, and if a credible region has adequate frequentist coverage. In this paper, we review the properties of Bayesian and related methods for several high-dimensional models such as many normal means problem, linear regression, generalized linear models, Gaussian and non-Gaussian graphical models. Effective computational approaches are also discussed.},
  language = {en}
}

@article{banischOpinionPolarizationLearning,
  title = {Opinion Polarization by Learning from Social Feedback},
  author = {Banisch, S. and Olbrich, E.},
  doi = {10.1080/0022250X.2018.1517761},
  abstract = {\textbf{ABSTRACT}{$<$}/p{$><$}p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table"{$>$}We explore a new mechanism to explain polarization phenomena in opinion dynamics in which agents evaluate alternative views on the basis of the social feedback obtained on expressing them. High support of the favored opinion in the social environment is treated as a positive feedback which reinforces the value associated to this opinion. In connected networks of sufficiently high modularity, different groups of agents can form strong convictions of competing opinions. Linking the social feedback process to standard equilibrium concepts we analytically characterize sufficient conditions for the stability of bi-polarization. While previous models have emphasized the polarization effects of deliberative argument-based communication, our model highlights an affective experience-based route to polarization, without assumptions about negative influence or bounded confidence.},
  journal = {Journal of Mathematical Sociology}
}

@article{banischOpinionPolarizationLearninga,
  title = {Opinion Polarization by Learning from Social Feedback},
  author = {Banisch, S. and Olbrich, E.},
  doi = {10.1080/0022250X.2018.1517761},
  abstract = {\textbf{ABSTRACT}{$<$}/p{$><$}p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table"{$>$}We explore a new mechanism to explain polarization phenomena in opinion dynamics in which agents evaluate alternative views on the basis of the social feedback obtained on expressing them. High support of the favored opinion in the social environment is treated as a positive feedback which reinforces the value associated to this opinion. In connected networks of sufficiently high modularity, different groups of agents can form strong convictions of competing opinions. Linking the social feedback process to standard equilibrium concepts we analytically characterize sufficient conditions for the stability of bi-polarization. While previous models have emphasized the polarization effects of deliberative argument-based communication, our model highlights an affective experience-based route to polarization, without assumptions about negative influence or bounded confidence.},
  journal = {Journal of Mathematical Sociology}
}

@article{bansakComparativeCausalMediationundefined/ed,
  title = {Comparative {{Causal Mediation}} and {{Relaxing}} the {{Assumption}} of {{No Mediator}}\textendash{{Outcome Confounding}}: {{An Application}} to {{International Law}} and {{Audience Costs}}},
  shorttitle = {Comparative {{Causal Mediation}} and {{Relaxing}} the {{Assumption}} of {{No Mediator}}\textendash{{Outcome Confounding}}},
  author = {Bansak, Kirk},
  year = {undefined/ed},
  pages = {1--22},
  issn = {1047-1987, 1476-4989},
  doi = {10.1017/pan.2019.31},
  abstract = {Experiments often include multiple treatments, with the primary goal to compare the causal effects of those treatments. This study focuses on comparing the causal anatomies of multiple treatments through the use of causal mediation analysis. It proposes a novel set of comparative causal mediation (CCM) estimands that compare the mediation effects of different treatments via a common mediator. Further, it derives the properties of a set of estimators for the CCM estimands and shows these estimators to be consistent (or conservative) under assumptions that do not require the absence of unobserved confounding of the mediator\textendash outcome relationship, which is a strong and nonrefutable assumption that must typically be made for consistent estimation of individual causal mediation effects. To illustrate the method, the study presents an original application investigating whether and how the international legal status of a foreign policy commitment can increase the domestic political ``audience costs'' that democratic governments suffer for violating such a commitment. The results provide novel evidence that international legalization can enhance audience costs via multiple causal channels, including by amplifying the perceived immorality of violating the commitment.},
  journal = {Political Analysis},
  language = {en}
}

@article{barabasiEmergenceScalingRandom1999,
  title = {Emergence of Scaling in Random Networks},
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@article{barabasiNetworkTakeover2012,
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  author = {Barab{\'a}si, Albert-L{\'a}szl{\'o}},
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  language = {en},
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}

@article{barabasiScaleFreeNetworksDecade2009,
  title = {Scale-{{Free Networks}}: {{A Decade}} and {{Beyond}}},
  shorttitle = {Scale-{{Free Networks}}},
  author = {Barab{\'a}si, Albert-L{\'a}szl{\'o}},
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@article{barandiaranDefiningCollectiveIdentities2020,
  title = {Defining {{Collective Identities}} in {{Technopolitical Interaction Networks}}},
  author = {Barandiaran, Xabier E. and {Calleja-L{\'o}pez}, Antonio and Cozzo, Emanuele},
  year = {2020},
  month = jul,
  volume = {11},
  pages = {1549},
  issn = {1664-1078},
  doi = {10.3389/fpsyg.2020.01549},
  abstract = {We are currently witnessing the emergence of new forms of collective identities and a redefinition of the old ones through networked digital interactions, and these can be explicitly measured and analyzed. We distinguish between three major trends on the development of the concept of identity in the social realm: (1) an essentialist sense (

license: MIT

repository: atomashevic/website-at

license_type: permissive

repo_name: atomashevic/website-at

branch_name: refs/heads/master

extension: bib