Paper: Analyzing Positions and Topics in Political Discussions of the German Bundestag

ACL ID P14-3004
Title Analyzing Positions and Topics in Political Discussions of the German Bundestag
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

We present ongoing doctoral work on au- tomatically understanding the positions of politicians with respect to those of the party they belong to. To this end, we use textual data, namely transcriptions of po- litical speeches from meetings of the Ger- man Bundestag, and party manifestos, in order to automatically acquire the posi- tions of political actors and parties, respec- tively. We discuss a variety of possible su- pervised and unsupervised approaches to determine the topics of interest and com- pare positions, and propose to explore an approach based on topic modeling tech- niques for these tasks.