
arXiv: 2505.09806
Voting advice applications (VAAs), which have become increasingly prominent in European elections, are seen as a successful tool for boosting electorates' political knowledge and engagement. However, VAAs' complex language and rigid presentation constrain their utility to less-sophisticated voters. While previous work enhanced VAAs' click-based interaction with scripted explanations, a conversational chatbot's potential for tailored discussion and deliberate political decision-making remains untapped. Our exploratory mixed-method study investigates how LLM-based chatbots can support voting preparation. We deployed a VAA chatbot to 331 users before Germany's 2024 European Parliament election, gathering insights from surveys, conversation logs, and 10 follow-up interviews. Participants found the VAA chatbot intuitive and informative, citing its simple language and flexible interaction. We further uncovered VAA chatbots' role as a catalyst for reflection and rationalization. Expanding on participants' desire for transparency, we provide design recommendations for building interactive and trustworthy VAA chatbots.
Accepted to ACM CUI 2025
ddc:004, FOS: Computer and information sciences, Computer Science - Computers and Society, Deliberation, Computers and Society (cs.CY), ddc:300, Computer Science - Human-Computer Interaction, Voting Advice Applications, Civic Education, Chatbot, Trustworthiness, Human-Computer Interaction (cs.HC)
ddc:004, FOS: Computer and information sciences, Computer Science - Computers and Society, Deliberation, Computers and Society (cs.CY), ddc:300, Computer Science - Human-Computer Interaction, Voting Advice Applications, Civic Education, Chatbot, Trustworthiness, Human-Computer Interaction (cs.HC)
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