Why does the competitiveness of an election affect voter turnout? Previous research has focused on elite behavior in mobilizing political participation and voters' altered assessments about the importance of their vote. However, I argue that exposure to political competition activates voters' emotions---which in turn affect the decision to turnout---and that individual differences in threat sensitivity moderate this mediated relationship. After first elaborating a theory for these relationships, I use data from the 2008 National Election Study to demonstrate that heightened electoral competitiveness is associated with stronger emotional evaluations of the presidential candidates. To further elucidate the relationships, I collect a sample of 113 million status messages posted on the online social networking site Facebook during the 2008 presidential election. Automated content analysis reveals that users living in competitive "battleground" states are more likely to express emotion when they discuss politics on the site, and that emotional activation in status messages partially mediates the relationship between exposure to competition and self-reported voting. I next explore whether a genetic sensitivity to threat conditions the way that exposure to political contention affects voter turnout. The nascent genopolitics literature theorizes that genetic, psychological, and physiological differences should be integral in interpreting political stimuli from the environment, but there have been few empirical confirmations of this expectation. I find in two distinct datasets that people who carry a version of a gene that makes them especially sensitive to social stress are more responsive to the level of contention in their political environment. I follow up on this finding with a mobilization field experiment designed to activate emotions toward political competition. My dissertation is one of the first attempts to identify the specific causal mechanisms that underlie the effects of individual biological differences on political outcomes. This research topic is relevant and timely: as our country continues to polarize and the consequences of people's emotional reactions to political disagreement intensify, it is important to understand the causal mechanisms that relate political contention to political behavior

Some social connections are stronger than others. People have not only friends, but also best friends. Social scientists have long recognized this characteristic of social connections and researchers frequently use the term tie strength to refer to this concept. We used online interaction data (specifically, Facebook interactions) to successfully identify real-world strong ties. Ground truth was established by asking users themselves to name their closest friends in real life. We found the frequency of online interaction was diagnostic of strong ties, and interaction frequency was much more useful diagnostically than were attributes of the user or the user's friends. More private communications (messages) were not necessarily more informative than public communications (comments, wall posts, and other interactions).

Researchers often face the problem of needing to protect the privacy of subjects while also needing to integrate data that contains personal information from diverse data sources. The advent of computational social science and the enormous amount of data about people that is being collected makes protecting the privacy of research subjects ever more important. However, strict privacy procedures can hinder the process of joining diverse sources of data that contain information about specific individual behaviors. In this paper we present a procedure to keep information about specific individuals from being "leaked" or shared in either direction between two sources of data without need of a trusted third party. To achieve this goal, we randomly assign individuals to anonymous groups before combining the anonymized information between the two sources of data. We refer to this method as the Yahtzee procedure, and show that it performs as predicted by theoretical analysis when we apply it to data from Facebook and public voter records.

Many critics raise concerns about the prevalence of echo chambers on social media and their potential role in increasing political polarization. However, the lack of available data and the challenges of conducting large-scale field experiments have made it difficult to assess the scope of the problem1,2. Here we present data from 2020 for the entire population of active adult Facebook users in the USA showing that content from like-minded sources constitutes the majority of what people see on the platform, although political information and news represent only a small fraction of these exposures. To evaluate a potential response to concerns about the effects of echo chambers, we conducted a multi-wave field experiment on Facebook among 23,377 users for whom we reduced exposure to content from like-minded sources during the 2020 US presidential election by about one-third. We found that the intervention increased their exposure to content from cross-cutting sources and decreased exposure to uncivil language, but had no measurable effects on eight preregistered attitudinal measures such as affective polarization, ideological extremity, candidate evaluations and belief in false claims. These precisely estimated results suggest that although exposure to content from like-minded sources on social media is common, reducing its prevalence during the 2020 US presidential election did not correspondingly reduce polarization in beliefs or attitudes.

We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 wk before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero.