TopFish: topic-based analysis of political position in US electoral campaigns
Federico Nanni, Cäcilia Zirn, Goran Glavaš, Jason Eichorst, Simone Paolo Ponzetto · MADOC (University of Mannheim) · 2016
In this paper we present TopFish, a multilevel computational method that integrates topic detection and political scaling and shows its applicability for a temporal aspect analysis of political campaigns (preprimary elections, primary elections, and general elections). It enables researchers to perform a range of multidimensional empirical analyses, ultimately allowing them to better understand how candidates position themselves during elections, with respect to a specific topic. The approach has been employed and tested on speeches from the 2008, 2012, and the (ongoing) 2016 US presidential campaigns.