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Conference paper · CUI '26 · 2026

Towards a Typology of User Engagement in Conversational Agent Voting Advice Applications

Daan van der Weijden, Thilo Ignaz Dieing, Fynn Bachmann

ACM Conference on Conversational User Interfaces (CUI '26), Bremen, Germany, 2026 · To appear

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Abstract

Voting Advice Applications (VAAs) help citizens align with political parties, but are limited by frequent comprehension problems. Conversational Agent VAAs (CAVAAs) address this by integrating chatbot-based support. Yet, user interaction patterns and their effects on completing the CAVAA remain underexplored. This study identifies behavior-based CAVAA user types and examines their interaction with chatbot personas. Using interaction data from 189 users of an GPT-driven CAVAA during the 2024 European Parliament elections, a Latent Class Analysis reveals three types: Checkers (low interaction), Seekers (high engagement and uncertainty), and Testers (system probing rather than advice seeking). While user types do not predict completion, the chatbot personas significantly did. We find that the more active chatbot (asking follow-up questions) increased dropout rates. Our analysis introduces a novel behavioral typology and highlights the importance of conversational design for reducing dropout and improving CAVAA effectiveness.

Cite

@inproceedings{vanderweijden2026towards,
  title={Towards a Typology of User Engagement in Conversational Agent Voting Advice Applications},
  author={van der Weijden, Daan and Dieing, Thilo Ignaz and Bachmann, Fynn},
  booktitle={Proceedings of the ACM Conference on Conversational User Interfaces (CUI '26)},
  year={2026},
  location={Bremen, Germany},
  numpages={7},
  publisher={Association for Computing Machinery},
  doi={10.1145/3816046.3816272}
}