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Voice Your Opinion! Young Voters’ Usage and Perceptions of a Text-Based, Voice-Based and Text-Voice Combined Conversational Agent Voting Advice Application (CAVAA)

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Chatbot Research and Design (CONVERSATIONS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13815))

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Abstract

Conversational Agent Voting Advice Applications (CAVAAs) are chatbot-based information retrieval systems for citizens who aim to inform themselves about the political issues at stake in times of political elections. Previous studies investigating these relatively young tools primarily focused on the effects of CAVAAs that include a text-based chatbot. In order to further optimize their design, current research compared the effects of CAVAAs with a text, voice, and combined chatbot. In an experimental lab study among young voters (N = 60) these three modalities have been compared on usage measures (the amount of information retrieved from the chatbot, and miscommunication), evaluation measures (ease of use, usefulness, and enjoyment), and political measures (perceived and factual political knowledge). Results show that the three CAVAA modalities score equally high on political measures and the perception of enjoyment. At the same time, the textual and combined CAVAA outperform the voice CAVAA on several aspects: the voice CAVAA received lower ease of use and usefulness scores, respondents requested less additional information, and they experienced more miscommunication when interacting with the voice chatbot. Analyses of the usage data also indicate that in the combined condition users hardly use the voice-option and instead almost exclusively rely on text-functionalities like clicking on suggestion buttons. This seems to suggest that using voice is too much of an effort for CAVAA users; we therefore recommend the usage of text-bots in this specific usage context.

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Notes

  1. 1.

    Data collection was initiated prior to final approval, following liaising with the ethics board.

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Acknowledgements

The authors would like to thank Tilburg University’s Fund (project number ESF2021–2) for the financial support to develop the CAVAAs. A summary of the results of this study has also been published in the Dutch popular-scientific magazine Tekstblad [22].

Author information

Authors and Affiliations

  1. Tilburg School of Humanities and Digital Sciences, Department of Communication and Cognition, Tilburg University, Tilburg, The Netherlands

    Christine Liebrecht, Naomi Kamoen & Celine Aerts

Authors
  1. Christine Liebrecht
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  2. Naomi Kamoen
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  3. Celine Aerts
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Corresponding author

Correspondence to Christine Liebrecht .

Editor information

Editors and Affiliations

  1. SINTEF, Oslo, Norway

    Asbjørn Følstad

  2. University of Amsterdam, Amsterdam, The Netherlands

    Theo Araujo

  3. CERTH-ITI, Thessaloniki, Greece

    Symeon Papadopoulos

  4. Durham University, Durham, UK

    Effie L.-C. Law

  5. University of Edinburgh, Edinburgh, UK

    Ewa Luger

  6. University of Agder, Grimstad, Norway

    Morten Goodwin

  7. University of Oslo, Oslo, Norway

    Petter Bae Brandtzaeg

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Liebrecht, C., Kamoen, N., Aerts, C. (2023). Voice Your Opinion! Young Voters’ Usage and Perceptions of a Text-Based, Voice-Based and Text-Voice Combined Conversational Agent Voting Advice Application (CAVAA). In: Følstad, A., et al. Chatbot Research and Design. CONVERSATIONS 2022. Lecture Notes in Computer Science, vol 13815. Springer, Cham. https://doi.org/10.1007/978-3-031-25581-6_3

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  • DOI: https://doi.org/10.1007/978-3-031-25581-6_3

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  • Online ISBN: 978-3-031-25581-6

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