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I Need a CAVAA: How Conversational Agent Voting Advice Applications (CAVAAs) Affect Users' Political Knowledge and Tool Experience
In election times, millions of voters consult Voting Advice Applications (VAAs) to learn more about political parties and their standpoints. While VAAs have been shown to enhance political knowledge and increase electoral turnout, research also demonstrates that voters frequently experience comprehe...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133695/ https://www.ncbi.nlm.nih.gov/pubmed/35647533 http://dx.doi.org/10.3389/frai.2022.835505 |
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author | Kamoen, Naomi Liebrecht, Christine |
author_facet | Kamoen, Naomi Liebrecht, Christine |
author_sort | Kamoen, Naomi |
collection | PubMed |
description | In election times, millions of voters consult Voting Advice Applications (VAAs) to learn more about political parties and their standpoints. While VAAs have been shown to enhance political knowledge and increase electoral turnout, research also demonstrates that voters frequently experience comprehension problems when responding to the political attitude statements in a VAA. We describe two studies in which we test a new type of VAA, called Conversational Agent VAA (CAVAA), in which users can easily access relevant information about the political issues in the VAA statements by asking questions to a chatbot. Study 1 reports about an online experiment (N = 229) with a 2 (Type: traditional VAA/CAVAA) x 2 (Political sophistication: low/high) design. Results show that CAVAA users report higher perceived political knowledge scores and also answer more factual knowledge questions correctly than users of a regular VAA. Also, participants' CAVAA experience was evaluated better. In Study 2 (N = 180), we compared three CAVAA designs (a structured design with buttons, a non-structured design with an open text field, and a semi-structured design with both buttons and an open text field), again for higher and lower politically sophisticated users. While the three designs score equally high on factual and perceived knowledge indicators, the experience of the structured CAVAA was evaluated more positively than the non-structured version. To explore the possible cause for these results, we conducted an additional qualitative content analysis on 90 chatbot-conversations (30 per chatbot version). This analysis shows that users more frequently access additional information in a structured design than in a non-structured design, whereas the number of break-offs is the same. This suggests that the structured design delivers the best experience, because it provides the best trigger to ask questions to the chatbot. |
format | Online Article Text |
id | pubmed-9133695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91336952022-05-27 I Need a CAVAA: How Conversational Agent Voting Advice Applications (CAVAAs) Affect Users' Political Knowledge and Tool Experience Kamoen, Naomi Liebrecht, Christine Front Artif Intell Artificial Intelligence In election times, millions of voters consult Voting Advice Applications (VAAs) to learn more about political parties and their standpoints. While VAAs have been shown to enhance political knowledge and increase electoral turnout, research also demonstrates that voters frequently experience comprehension problems when responding to the political attitude statements in a VAA. We describe two studies in which we test a new type of VAA, called Conversational Agent VAA (CAVAA), in which users can easily access relevant information about the political issues in the VAA statements by asking questions to a chatbot. Study 1 reports about an online experiment (N = 229) with a 2 (Type: traditional VAA/CAVAA) x 2 (Political sophistication: low/high) design. Results show that CAVAA users report higher perceived political knowledge scores and also answer more factual knowledge questions correctly than users of a regular VAA. Also, participants' CAVAA experience was evaluated better. In Study 2 (N = 180), we compared three CAVAA designs (a structured design with buttons, a non-structured design with an open text field, and a semi-structured design with both buttons and an open text field), again for higher and lower politically sophisticated users. While the three designs score equally high on factual and perceived knowledge indicators, the experience of the structured CAVAA was evaluated more positively than the non-structured version. To explore the possible cause for these results, we conducted an additional qualitative content analysis on 90 chatbot-conversations (30 per chatbot version). This analysis shows that users more frequently access additional information in a structured design than in a non-structured design, whereas the number of break-offs is the same. This suggests that the structured design delivers the best experience, because it provides the best trigger to ask questions to the chatbot. Frontiers Media S.A. 2022-05-12 /pmc/articles/PMC9133695/ /pubmed/35647533 http://dx.doi.org/10.3389/frai.2022.835505 Text en Copyright © 2022 Kamoen and Liebrecht. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Artificial Intelligence Kamoen, Naomi Liebrecht, Christine I Need a CAVAA: How Conversational Agent Voting Advice Applications (CAVAAs) Affect Users' Political Knowledge and Tool Experience |
title | I Need a CAVAA: How Conversational Agent Voting Advice Applications (CAVAAs) Affect Users' Political Knowledge and Tool Experience |
title_full | I Need a CAVAA: How Conversational Agent Voting Advice Applications (CAVAAs) Affect Users' Political Knowledge and Tool Experience |
title_fullStr | I Need a CAVAA: How Conversational Agent Voting Advice Applications (CAVAAs) Affect Users' Political Knowledge and Tool Experience |
title_full_unstemmed | I Need a CAVAA: How Conversational Agent Voting Advice Applications (CAVAAs) Affect Users' Political Knowledge and Tool Experience |
title_short | I Need a CAVAA: How Conversational Agent Voting Advice Applications (CAVAAs) Affect Users' Political Knowledge and Tool Experience |
title_sort | i need a cavaa: how conversational agent voting advice applications (cavaas) affect users' political knowledge and tool experience |
topic | Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133695/ https://www.ncbi.nlm.nih.gov/pubmed/35647533 http://dx.doi.org/10.3389/frai.2022.835505 |
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