Determining the Presence of Political Parties in Social Circles
Keywords:social networks, twitter, politics, political affiliation prediction, random walks, graphs
We derive the political climate of the social circles of Twitter users using a weakly-supervised approach. By applying random walks over a sub-sample of Twitter's social graph we infer a distribution indicating the presence of eight Flemish political parties in users' social circles in the months before the 2014 elections. The graph structure is induced through a combination of connection and retweet features and combines information of over a million tweets and 14 million follower connections. We solely exploit the social graph structure and do not rely on tweet content. For validation we compare the affiliation of politically active Twitter users with the most-influential party in their network. On a validation set of around 700 politically active individuals we achieve F_1 scores of 0.85 and greater. We asked the Twitter community to evaluate our classification performance. More than half of the 2258 users who responded reported a score higher than 60 out of 100.