What the study found
The study presents a definition of inter-party communication as public communication by parties about other parties, with a positive, neutral, or negative stance, and focused on collaboration, policy, or personal issues. It also reports that a transformer-based approach can automatically classify large volumes of text for this topic.
Why the authors say this matters
The authors conclude that this work deepens understanding of party competition, advances methods for automated text classification, and enables new research on political communication. The study suggests this is important because research on inter-party communication has been limited by unclear concepts and difficult large-scale measurement.
What the researchers tested
The researchers introduced a novel transformer-based approach, meaning a machine-learning text model based on a transformer architecture, to classify inter-party communication automatically. They tested it in case studies on coalition signals in Germany and negative campaigning in Austria.
What worked and what didn't
The abstract says the approach demonstrated effectiveness in the two case studies. It does not report specific accuracy values or describe any failed cases.
What to keep in mind
The available summary does not give detailed performance metrics, study size, or technical limitations. It also does not describe broader validation beyond the two case studies mentioned.
Key points
- Inter-party communication is defined as public communication by parties about other parties.
- The definition includes positive, neutral, and negative stances, and communication about collaboration, policy, or personal issues.
- A transformer-based approach was introduced to classify large volumes of political text automatically.
- Case studies examined coalition signals in Germany and negative campaigning in Austria.
- The abstract says the method was effective, but gives no specific performance numbers.
Disclosure
- Research title:
- Transformer method measures inter-party communication in politics
- Authors:
- Anna Adendorf, Oke Bahnsen, Thomas Gschwend, Lena Maria Huber, Simone Paolo Ponzetto, Ines Rehbein, Lukas F. Stoetzer
- Institutions:
- University of Mannheim, University of Mannheim, University of Mannheim, University of Mannheim, University of Mannheim, University of Mannheim, Witten/Herdecke University
- Publication date:
- 2026-02-24
- OpenAlex record:
- View
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