My dissertation addresses the relationship between social media usage and political polarization. As usage of social networking platforms like Facebook or Twitter grows, more individuals are exposed to news and opinions that are curated and framed by their personal networks. In contrast to previous studies, I argue that the consumption of political information through social media induces ideological moderation, because it increases exposure to politically diverse content generated by weak social ties, which tend to be more ideologically heterogeneous. To examine this question, I develop a new method to estimate dynamic ideological positions for political actors and citizens from their social media networks that replicate conventional measures of ideology. Combining evidence from survey and social media data in Germany, Spain, and the United States, I show that exposure to diverse political information on social media reduces political extremism.
Birds of the Same Feather Tweet Together. Bayesian Ideal Point Estimation Using Twitter Data.
The structure of the social networks in which political actors and citizens are embedded can be a source of information about their ideological positions. Expand abstract »
Politicians and citizens increasingly engage in political conversations on social media outlets such as Twitter. In this paper I show that the structure of the social networks in which they are embedded can be a source of information about their ideological positions. Under the assumption that social networks are homophilic, I develop a Bayesian Spatial Following model that considers ideology as a latent variable, whose value can be inferred by examining which politics actors each user is following. This method allows us to estimate ideology for more actors than any existing alternative, at any point in time and across many polities. I apply this method to estimate ideal points for a large sample of both elite and mass public Twitter users in the US and five European countries. Thee estimated positions of legislators and political parties replicate conventional measures of ideology. The method is also able to successfully classify individuals who state their political preferences publicly and a sample of users matched with their party registration records. To illustrate the potential contribution of these estimates, I examine the extent to which online behavior during the 2012 US presidential election campaign is clustered along ideological lines.
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Rooting out corruption or rooting for corruption? The Heterogenous Electoral Consequences of Scandals
Forthcoming in Political Science Research and Methods
.Co-authored with Pablo Fernández-Vázquez and Gonzalo Rivero.
Working paper, July 2014 | Expand abstract »
Corruption scandals have been found to have significant but mild electoral effects in the comparative literature (Golden, 2006). However, most studies have assumed that voters punish all kinds of illegal practices. This article challenges this assumption by distinguishing between two types of corruption, according to the type of welfare consequences they have for the constituency. This hypothesis is tested using data from the 2011 Spanish local elections. We exploit the abundance of corruption allegations associated with the Spanish housing boom, which generated income gains for a wide segment of the electorate in the short-term. We find that voters ignore corruption when there are side benefits to it, and that punishment is only administered in those cases in which they do not receive compensation.
Understanding the political representativeness of Twitter users.
Forthcoming in Social Science Computer Review.
Co-authored with Gonzalo Rivero.
Link | Pre-print | Expand abstract »
In this article we analyze the structure and content of the political conversations that took place through the micro-blogging platform Twitter in the context of the 2011 Spanish legislative elections and the 2012 US presidential elections. Using a unique database of nearly 70 million tweets collected during both election campaigns, we find that Twitter replicates most of the existing inequalities in public political exchanges. Twitter users who write about politics tend to be male, to live in urban areas, and to have extreme ideological preferences. Our results have important implications for future research on the relationship between social media and politics, since they highlight the need to correct for potential biases derived from these sources of inequality.
Social Media and Political Communication: A survey of Twitter users during the 2013 Italian general election
Italian Political Science Review
, 2013.Co-authored with Cristian Vaccari, Augusto Valeriani, Richard Bonneau, John T. Jost, Jonathan Nagler, and Joshua Tucker.
Link | Expand abstract »
Social media have become increasingly relevant in election campaigns, as both politicians and citizens have integrated them into their communication repertoires. However, little is known about which types of citizens employ these tools to discuss politics and stay informed about current affairs and how they integrate the contents and connections they encounter online with their offline repertoires of political action. In order to address these questions, we devised an innovative online survey involving a random sample representative of Italians who communicated about the 2013 general election on Twitter. Our results show that Twitter political users in Italy are disproportionately male, younger, better educated, more interested in politics, and ideologically more left-wing than the population as a whole. Moreover, there is a strong correlation between online and offline political communication, and Twitter users often relay the political contents they encounter on the web in their face-to-face conversations. Although the political users of social media are not representative of the population, their greater propensity to engage in political conversations both online and offline make them important channels of personal communication and allow the contents that circulate on the web to diffuse among populations that are much broader than those that engage with social media. The electoral significance of these digital platforms thus reaches well beyond the immediate audiences that are exposed to political contents through them.
Leaders or Followers? Measuring Political Responsiveness in the U.S. Congress Using Social Media Data.
Co-authored with Richard Bonneau, Patrick Egan, John T. Jost, Jonathan Nagler and Joshua Tucker
Working paper, June 2014 | Expand abstract »
Are legislators responsive to their constituents in their public communication? To what extent are they able to shape the agenda that the mass public cares about, as expressed by the issues they discuss? We address this twofold question with an analysis of all tweets sent by Members of the U.S. Congress and a random sample of their followers from January 2013 to March 2014. Using a Latent Dirichlet Allocation model, we extract topics that represent the diversity of issues that legislators and ordinary citizens discuss on this social networking site. Then, we exploit variation in the distribution of topics over time to test whether Members of Congress lead or follow their constituents in their selection of issues to discuss, employing a Granger-causality frame- work. We find that legislators are responsive in their public statements to their constituents, but also that they have limited influence on their followers’ public agenda. To further understand the mechanisms that explain political responsiveness, we also examine whether Members of Congress are more responsive to specific constituents groups, showing that they are more influenced by co-partisans, politically interested citizens, and social media users located within their constituency.
Vague concepts in survey questions:
A general problem illustrated with the left-right scale.
Co-authored with Paul Bauer, Kathrin Ackermann and Aaron Venetz.
Working paper, June 2014 | Expand abstract »
This study aims at pointing at an important problem: Vague concepts in survey questions may trigger differential associations and, thus, impact respondents’ answers. If these associations vary systematically with other explanatory variables it may introduce bias in observed empirical relationships. We illustrate this problem relying on a survey of 3467 Germans that were asked probing questions regarding the concepts left and right after placing themselves on the left-right scale. We find that individuals attribute very different meanings to the concepts “left” and “right”. This seems to impact measurement values on the left-right scale. In addition, our results provide evidence that associations are systematic in nature, which could bias the effects of other explanatory variables. These results indicate that the interpersonal comparability of this measurement instrument (the left-right scale) across individuals is impaired. We discuss various solutions and recommend replacing the left-right scale with a battery of questions about issues with more specific ideological content in future surveys. Our findings have important implications for survey research in general, and underscore the necessity to investigate to what extent “vague” concepts mean the same for different individuals that belong to the target population.
Issue and Event Specific Dynamics of Ideological
Co-authored with Richard Bonneau, John T. Jost, Jonathan Nagler and Joshua Tucker
Cover page, September 2014 | Expand abstract »
Models of social and political behavior require precise estimates of the ideological positions of elite political actors and ordinary citizens. Social media presents unparalleled opportunities to measure individual traits of millions of people. Here we extend existing models that estimate positions on latent spaces based on network structure to estimate the ideological preferences of 3.8 million Twitter users in the United States. We then examine the role of political ideology in information diffusion through a dataset of 150 million tweets related to 12 different political and non-political issues. Results reveal that communication structures are dynamic, flexible, and situation-specific, and that previous work may overestimate the degree of online political polarization. We demonstrate that newsworthy events unrelated to politics and emergency situations are able to dramatically reduce the degree of ideological segregation in online communication networks, suggesting that it is a mistake to consider ideological polarization as a fixed aspect of online communication. These findings underscore the promise of harvesting social media data bearing on self-selected networks to estimate individual-level characteristics, as well as the potential for developing dynamic indicators of ideological preferences that will enable researchers to address a wide range of existing questions about social and political behavior.
The Empirical Determinants of Social Media Adoption by World Leaders and its Empirical Consequences.
Co-authored with Thomas Zeitzoff
Working paper, August 2014 | Expand abstract »
An important component of leader behavior is the strategic use of communication to both domestic and international audiences. Social media, and in particular Twitter, has emerged as an import new medium for political communication Over 80% of world leaders have an active presence on the micro-blogging website Twitter. In this paper we explore which factors explain when leaders and governments choose to adopt Twitter as a means of a communication. We look at variation across levels of democratization and election timing to understand differential adoption. We find that both electoral timing and democracy strongly influence adoption of Twitter. Furthermore, we exploit this source of information to better understand the way in which governments try to communicate with their citizens and the international community. Finally, we develop a Bayesian ideal point estimation method using shared Twitter follower networks to locate world leaders on an underlying multidimensional space. We demonstrate that distances between leaders on this space are excellent predictors of bilateral trade volume, even after controlling for common determinants of trade, and argue that they better capture affinities between countries in international affairs.
NYU PhD Course "Quantitative Methods for Political Science 3"
See this GitHub repository for recitation materials on maximum likelihood, duration models, time-series analysis, and Bayesian statistics.
NYU-Abu Dhabi Course "Social Media and Political Participation"
The recitation materials for the course, available on this GitHub repository, provide an introduction to statistical analysis using R, and show how to harvest and analyze data from Twitter and Facebook.