The use of social media has become increasingly widespread among citizens and politicians in Brazil. This means of communication served as a key arena for debate and propaganda during the 2014 legislative and presidential elections, when a very polarized political scenario emerged. New approaches have been developed that use information from the social network structure constructed by political actors on social media platforms, such as Twitter, in order to calculate ideal points. Can data from the decision to 'follow' a profile on Twitter be used to estimate politicians' ideological positions? Can approaches like this show the variance of political positions even within a very fragmented legislative body, such as the Brazilian Chamber of Deputies? This article presents and analyzes the successful application of a Bayesian spatial model developed by Barberá (2015), using data from Brazil. This method allowed to capture differences between parties and political actors similar to those found by means of roll call votes. It also makes possible to calculate ideal points for actors who participate in the public debate, but are not professional politicians.
