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

Viral Replication Rate Regulates Clinical Outcome and CD8 T Cell Responses during Highly Pathogenic H5N1 Influenza Virus Infection in Mice

Since the first recorded infection of humans with H5N1 viruses of avian origin in 1997, sporadic human infections continue to occur with a staggering mortality rate of >60%. Although sustained human-to-human transmission has not occurred yet, there is a growing concern that these H5N1 viruses might acquire this trait and raise the specter of a pandemic. Despite progress in deciphering viral determinants of pathogenicity, we still lack crucial information on virus/immune system interactions pertaining to severe disease and high mortality associated with human H5N1 influenza virus infections. Using two human isolates of H5N1 viruses that differ in their pathogenicity in mice, we have defined mechanistic links among the rate of viral replication, mortality, CD8 T cell responses, and immunopathology. The extreme pathogenicity of H5N1 viruses was directly linked to the ability of the virus to replicate rapidly, and swiftly attain high steady-state titers in the lungs within 48 hours after infection. The remarkably high replication rate of the highly pathogenic H5N1 virus did not prevent the induction of IFN-β or activation of CD8 T cells, but the CD8 T cell response was ineffective in controlling viral replication in the lungs and CD8 T cell deficiency did not affect viral titers or mortality. Additionally, BIM deficiency ameliorated lung pathology and inhibited T cell apoptosis without affecting survival of mice. Therefore, rapidly replicating, highly lethal H5N1 viruses could simply outpace and overwhelm the adaptive immune responses, and kill the host by direct cytopathic effects. However, therapeutic suppression of early viral replication and the associated enhancement of CD8 T cell responses improved the survival of mice following a lethal H5N1 infection. These findings suggest that suppression of early H5N1 virus replication is key to the programming of an effective host response, which has implications in treatment of this infection in humans

Simplification and Shift in Cognition of Political Difference: Applying the Geometric Modeling to the Analysis of Semantic Similarity Judgment

Perceiving differences by means of spatial analogies is intrinsic to human cognition. Multi-dimensional scaling (MDS) analysis based on Minkowski geometry has been used primarily on data on sensory similarity judgments, leaving judgments on abstractive differences unanalyzed. Indeed, analysts have failed to find appropriate experimental or real-life data in this regard. Our MDS analysis used survey data on political scientists' judgments of the similarities and differences between political positions expressed in terms of distance. Both distance smoothing and majorization techniques were applied to a three-way dataset of similarity judgments provided by at least seven experts on at least five parties' positions on at least seven policies (i.e., originally yielding 245 dimensions) to substantially reduce the risk of local minima. The analysis found two dimensions, which were sufficient for mapping differences, and fit the city-block dimensions better than the Euclidean metric in all datasets obtained from 13 countries. Most city-block dimensions were highly correlated with the simplified criterion (i.e., the left–right ideology) for differences that are actually used in real politics. The isometry of the city-block and dominance metrics in two-dimensional space carries further implications. More specifically, individuals may pay attention to two dimensions (if represented in the city-block metric) or focus on a single dimension (if represented in the dominance metric) when judging differences between the same objects. Switching between metrics may be expected to occur during cognitive processing as frequently as the apparent discontinuities and shifts in human attention that may underlie changing judgments in real situations occur. Consequently, the result has extended strong support for the validity of the geometric models to represent an important social cognition, i.e., the one of political differences, which is deeply rooted in human nature

Party ideology and legislative agendas: Estimating contextual policy positions for the study of EU decision-making

This article introduces a novel approach for generating agenda-related estimates of the policy positions of political parties from party manifestos and expert surveys. We show that current party estimates provide for little variation across policy areas and over time. In response, we propose to relate the issue-specific ideological preference profiles of political parties to the legislative context. For the dimensional representation of policy positions of political parties our procedure weights the issue-specific preference profiles by their prominence on the agenda of each policy area. We apply this procedure to EU legislation and locate national political parties on a national/supranational and left/right dimension, which can be used for the analysis of Council decision-making