Affiliation:
1. Humboldt-Universitat zu Berlin, Berlin, Germany
2. Universität Witten/Herdecke, Witten, Germany
Abstract
We present the PARTYPRESS Database, which compiles more than 250,000 published press releases from 68 parties in 9 European countries. The database covers the press releases of the most relevant political parties in these countries from 2010 onward. It provides a supervised machine learning classification of press releases into 21 unique issue categories according to a general codebook. The PARTYPRESS Database can be used to study parties’ issue agendas comparatively and over time. We extend a recent analysis in Gessler and Hunger (2022) to illustrate the usefulness of the database in studying dynamic party competition, communication, and behavior.
Funder
Deutsche Forschungsgemeinschaft
Subject
Political Science and International Relations,Public Administration,Sociology and Political Science