15:30 - 17:45
Friday-Panel
Chair/s:
Thomas Gschwend
Discussant/s:
Shared by Panellists
Meeting Room M

Natalia Umansky
Repost and Like: Securitization Theory in the Digital Age

Rosa M. Navarrete, Anna Adendorf, Markus Baumann
Tweeting out loud. Coalition signals in social media

Anna Adendorf, Ines Rehbein, Oke Bahnsen, Thomas Gschwend, Simone Paolo Ponzetto
Who wants to go with whom? Identifying coalition signals in newspaper articles using supervised machine learning

David Moore
Explaining the Variation in Individuals' Conspiratorial Beliefs: The Effect of Exposure to Emotive Conspiratorial Messaging in the Media
Who wants to go with whom? Identifying coalition signals in newspaper articles using supervised machine learning
Anna Adendorf 1, Ines Rehbein 2, Oke Bahnsen 1, Thomas Gschwend 1, Simone Paolo Ponzetto 2
1 University of Mannheim, Mannheim Centre for European Social Research
2 University of Mannheim, Data and Web Science Group, School of Business Informatics and Mathematics

During election campaigns party elites often communicate which coalition they might or might not be willing to enter after the election. These public statements about prospects of future governments are often picked up by media outlets. In this paper, we present a supervised learning model to classify coalition signals in newspaper articles. The method identifies segments of text in which an affiliate of one party rules out or promotes a coalition with another party. We evaluate our approach based on hand-coded newspaper articles in Germany and Austria and validate the method based on pre-electoral coalitions in state elections. Both applications reveal the advantages of our method over existing dictionary approaches. Research can use our approach when interested in identifying targeted party elite communication about a specific subject in newspaper articles.