Inferring Population Preferences via Mixtures of Spatial Voting Models

Understanding political phenomena requires measuring the political preferences of society. We introduce a model based on mixtures of spatial voting models that infers the underlying distribution of political preferences of voters with only voting records of the population and political positions of candidates in an election. Beyond offering a cost-effective alternative to surveys, this method projects the political preferences of voters and candidates into a shared latent preference space. This projection allows us to directly compare the preferences of the two groups, which is desirable for political science but difficult with traditional survey methods. After validating the aggregated-level inferences of this model against results of related work and on simple prediction tasks, we apply the model to better understand the phenomenon of political polarization in the Texas, New York, and Ohio electorates. Taken at face value, inferences drawn from our model indicate that the electorates in these states may be less bimodal than the distribution of candidates, but that the electorates are comparatively more extreme in their variance. We conclude with a discussion of limitations of our method and potential future directions for research.Comment: To be published in the 8th International Conference on Social Informatics (SocInfo) 201

How Polarized Have We Become? A Multimodal Classification of Trump Followers and Clinton Followers

Polarization in American politics has been extensively documented and analyzed for decades, and the phenomenon became all the more apparent during the 2016 presidential election, where Trump and Clinton depicted two radically different pictures of America. Inspired by this gaping polarization and the extensive utilization of Twitter during the 2016 presidential campaign, in this paper we take the first step in measuring polarization in social media and we attempt to predict individuals' Twitter following behavior through analyzing ones' everyday tweets, profile images and posted pictures. As such, we treat polarization as a classification problem and study to what extent Trump followers and Clinton followers on Twitter can be distinguished, which in turn serves as a metric of polarization in general. We apply LSTM to processing tweet features and we extract visual features using the VGG neural network. Integrating these two sets of features boosts the overall performance. We are able to achieve an accuracy of 69%, suggesting that the high degree of polarization recorded in the literature has started to manifest itself in social media as well.Comment: 16 pages, SocInfo 2017, 9th International Conference on Social Informatic

Analyzing Ideological Communities in Congressional Voting Networks

We here study the behavior of political party members aiming at identifying how ideological communities are created and evolve over time in diverse (fragmented and non-fragmented) party systems. Using public voting data of both Brazil and the US, we propose a methodology to identify and characterize ideological communities, their member polarization, and how such communities evolve over time, covering a 15-year period. Our results reveal very distinct patterns across the two case studies, in terms of both structural and dynamic properties

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure

The South, the suburbs, and the Vatican too: explaining partisan change among Catholics

This paper explains changes in partisanship among Catholics in the last quarter of the 20th Century using a theory of partisan change centered on the contexts in which Catholics lived. Catholics were part of the post-New Deal Democratic coalition, but they have become a swing demographic group. We argue that these changes in partisanship are best explained by changes in elite messages that are filtered through an individual’s social network. Those Catholics who lived or moved into the increasingly Republican suburbs and South were the Catholics who were most likely to adopt a non-Democratic partisan identity. Changes in context better explain Catholic partisanship than party abortion policy post Roe v. Wade or ideological sorting. We demonstrate evidence in support of our argument using the ANES cumulative file from 1972 through 2000

What explains electoral responses to the 'Great Recession in Europe?

The ?Great Recession? in Europe started in early 2008 and was the greatest economic crisis facing the continent since the Great Depression of the 1930s. It produced a largescale loss of support for many incumbent parties. The purpose of this paper is to explain responses to the crisis among European electorates with the assistance of three rival models of electoral choice. The first is the cleavages model associated with Rokkan and Lipset which highlights the importance of social groups as the sources of electoral support. The second is the spatial model of party competition which focuses on the ideological distance between voters and parties in relation to divisive issues in society. The third is the valence model which argues that voters will support parties that deliver policies over which there is widespread agreement about what should be done. The paper models electoral support for incumbent parties using data from the European Social Surveys of 2006, conducted prior to the recession, and again in 2012 some four years into the crisis. The results show that all three models are relevant for understanding mass political responses to the crisis. It is also apparent that an ideological shift to the right occurred in electoral support between the two periods and this happened among both the voters and also the incumbent parties in Europe

Corruption and bicameral reforms

During the last decade unicameral proposals have been put forward in fourteen US states. In this paper we analyze the effects of the proposed constitutional reforms, in a setting where decision making is subject to ‘hard time constraints’, and lawmakers face the opposing interests of a lobby and the electorate. We show that bicameralism might lead to a decline in the lawmakers’ bargaining power vis-a-vis the lobby, thus compromising their accountability to voters. Hence, bicameralism is not a panacea against the abuse of power by elected legislators and the proposed unicameral reforms could be effective in reducing corruption among elected representatives

Ideological Labels in America

This paper extends Ellis and Stimson’s (Ideology in America. New York: Cambridge UniversityPress, 2012) study of the operational-symbolic paradox using issue-level measures of ideological incongruence based on respondent positions and symbolic labels for these positions across 14 issues. Like Ellis and Stimson, we find that substantial numbers—over 30 %—of Americans experience conflicted conservatism. Our issue-level data reveal, furthermore, that conflicted conservatism is most common on the issues of education and welfare spending. In addition, we also find that 20 % of Americans exhibit conflicted liberalism. We then replicate Ellis and Stimson’s finding that conflicted conservatism is associated with low sophistication and religiosity, but also find that it is associated with being socialized in a post-1960s generation and using Fox News as a main news source. Finally, we show the important role played by identities, with both conflicted conservatism and conflicted liberalism linked with partisan and ideological identities, and conflicted liberalism additionally associated with ethnic identities

Antibody Repertoires in Humanized NOD-scid-IL2Rγnull Mice and Human B Cells Reveals Human-Like Diversification and Tolerance Checkpoints in the Mouse

Immunodeficient mice reconstituted with human hematopoietic stem cells enable the in vivo study of human hematopoiesis. In particular, NOD-scid-IL2Rγnull engrafted mice have been shown to have reasonable levels of T and B cell repopulation and can mount T-cell dependent responses; however, antigen-specific B-cell responses in this model are generally poor. We explored whether developmental defects in the immunoglobulin gene repertoire might be partly responsible for the low level of antibody responses in this model. Roche 454 sequencing was used to obtain over 685,000 reads from cDNA encoding immunoglobulin heavy (IGH) and light (IGK and IGL) genes isolated from immature, naïve, or total splenic B cells in engrafted NOD-scid-IL2Rγnull mice, and compared with over 940,000 reads from peripheral B cells of two healthy volunteers. We find that while naïve B-cell repertoires in humanized mice are chiefly indistinguishable from those in human blood B cells, and display highly correlated patterns of immunoglobulin gene segment use, the complementarity-determining region H3 (CDR-H3) repertoires are nevertheless extremely diverse and are specific for each individual. Despite this diversity, preferential DH-JH pairings repeatedly occur within the CDR-H3 interval that are strikingly similar across all repertoires examined, implying a genetic constraint imposed on repertoire generation. Moreover, CDR-H3 length, charged amino-acid content, and hydropathy are indistinguishable between humans and humanized mice, with no evidence of global autoimmune signatures. Importantly, however, a statistically greater usage of the inherently autoreactive IGHV4-34 and IGKV4-1 genes was observed in the newly formed immature B cells relative to naïve B or total splenic B cells in the humanized mice, a finding consistent with the deletion of autoreactive B cells in humans. Overall, our results provide evidence that key features of the primary repertoire are shaped by genetic factors intrinsic to human B cells and are principally unaltered by differences between mouse and human stromal microenvironments