Political polarization is traditionally analyzed through the ideological stances of groups and parties, but it also has a behavioral component that manifests in the interactions between individuals. We present an empirical analysis of the digital traces of politicians in politnetz.ch, a Swiss online platform focused on political activity, in which politicians interact by creating support links, comments, and likes. We analyze network polarization as the level of intra-party cohesion with respect to inter-party connectivity, finding that supports show a very strongly polarized structure with respect to party alignment. The analysis of this multiplex network shows that each layer of interaction contains relevant information, where comment groups follow topics related to Swiss politics. Our analysis reveals that polarization in the layer of likes evolves in time, increasing close to the federal elections of 2011. Furthermore, we analyze the internal social network of each party through metrics related to hierarchical structures, information efficiency, and social resilience. Our results suggest that the online social structure of a party is related to its ideology, and reveal that the degree of connectivity across two parties increases when they are close in the ideological space of a multi-party system.
Internet voting (i-voting) is often discussed as a potential remedy against declining turnout rates. This paper presents new evidence on the causal effect of i-voting on turnout, drawing on trials conducted in two Swiss cantons: Geneva and Zurich. Both Geneva and Zurich constitute hard cases for i-voting, given that i-voting was introduced in the presence of postal voting. However, this setting allows us to test some of the more optimistic claims regarding i-voting's ability to increase turnout. Empirically, we exploit the advantageous circumstance that federal legislation created a situation coming close to a natural experiment, with some of Geneva's and Zurich's municipalities participating in i-voting trials and others not. Using difference-indifferences estimation, we find that i-voting did not increase turnout in the cantons of Geneva and Zurich.
Low-dimensional spatial representations of political preferences are a widespread feature of voting advice applications (VAAs). Currently, VAA spatial maps tend to be defined on the basis of a priori reasoning. This article argues that VAA spatial maps should be empirically validated to safeguard fundamental psychometric properties -in particular, unidimensionality and reliability. We suggest dynamic scale validation as a pragmatic method for improving measurement quality in VAA spatial maps. The basic logic of dynamic scale validation is to exploit early user data as a benchmark against which ex-ante defined maps can be evaluated. We draw on data from one of the most institutionalised VAA settings, Switzerland, to illustrate this dynamic approach to scale validation.
We present our approach to online popularity and its applications to political science, aiming at the creation of agentbased models that reproduce patterns of popularity in participatory media. We illustrate our approach analyzing a dataset from Youtube, composed of the view statistics and comments for the videos of the U.S. presidential campaigns of 2008 and 2012. Using sentiment analysis, we quantify the collective emotions expressed by the viewers, finding that democrat campaigns elicited more positive collective emotions than republican campaigns. Techniques from computational social science allow us to measure virality of the videos of each campaign, to find that democrat videos are shared faster but republican ones are remembered longer inside the community. Last we present our work in progress in voting advice applications, and our results analyzing the data from choose4greece.com. We show how we assess the policy differences between parties and their voters, and how voting advice applications can be extended to test our agentbased models.
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