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Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data
Politicians and citizens increasingly engage in political conversations on social media, so how can the structure of social networks be a source of information about a person’s ideological position? We find that during the 2012 U.S. presidential election legislators did align their tweets with how they were voting on legislation.
Citation
Barberá, Pablo. “Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data.” Political Analysis 23, no. 1 (2015): 76–91. https://doi.org/10.1093/pan/mpu011
Date Posted
Dec 01, 2015
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Abstract
Politicians and citizens increasingly engage in political conversations on social media outlets such as Twitter. In this article, 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 United States and five European countries. The 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 U.S. presidential election campaign is clustered along ideological lines.
Background
Twitter has become one of the most important communication arenas in daily politics. Most studies estimate ideal points (or the position of each legislator on the left-right or other dimensions using the votes that they cast on legislation) for legislators only, and when the analysis also includes voters, it is done at the expense of strong "bridging" assumptions, or only for self-selected population groups. Politicians and citizens increasingly engage in political conversations on social media, so how can the structure of social networks be a source of information about a person’s ideological position?
Study
Under the assumption that social networks are typically used for people to maintain relationships with people who are similar to themselves, we develop a model that considers ideology as a hidden variable, whose value can be inferred by examining which political actors a person 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.
Results
To illustrate a potential use of these estimates, we examine the extent to which online behavior during the 2012 U.S. presidential election campaign is clustered along ideological lines, finding support for the so-called "echo-chamber" theory and high levels of political polarization at the mass. We apply this method to a large sample of both elite and mass public Twitter users in the United States and five European countries. The method is successful in classifying individuals who state their political preferences publicly and a sample of users matched with their party registration records.