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Data · dataset · 2025

Enhancing Voter Decision-Making: The Impact of Proactive and Reactive Chatbots in Voting Advice Applications

Listed in IISH Dataverse and ODISSEI Portal — shown once because both records carry DOI 10.34894/yzsd50

Previous research has shown that voters often struggle to understand political statements in Voting Advice Applications (VAAs) and tend to make minimal efforts to resolve these comprehension difficulties.

Description

Conversational Agent Voting Advice Applications (CAVAAs) present a promising solution by incorporating chatbots that provide users with additional information at low cognitive cost. This study investigates an experiment conducted in the lead-up to the Dutch National Elections on November 22, 2023, comparing a standard VAA without supplementary information to two CAVAA versions: one with a proactive chatbot that initiates interactions and one with a reactive chatbot that responds to user queries.

A total of 148 university students were randomly assigned to one of the three conditions. Results revealed that information options in the two CAVAA conditions were used extensively, with information being requested in about 45% of the cases. Participants primarily sought opinion-based information, followed by details on the status quo, and lastly, semantic clarification of terms.

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This suggests that voters are not just searching for objective facts but also for argumentative insights. Comparing the two CAVAA conditions to the regular VAA, both CAVAA versions showed a reduced proportion of non-directional responses, indicating that chatbots effectively help users resolve comprehension issues. Furthermore, while all tools were rated similarly in terms of ease of use and playfulness, CAVAA users found the tool more useful and they also felt better informed.

These improvements were largely consistent across both proactive and reactive chatbot versions, suggesting that CAVAAs can enhance the quality of voter decision-making, regardless of the chatbot’s engagement style.

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Stated by source
Social Sciences · Social Sciences
Provenance · 2 source records, 12 field assertions
SourceKeyLast seenRaw
IISH Dataversedoi:10.34894/YZSD5012 d agoJSON v1
ODISSEI Portaldoi:10.34894/YZSD508 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].dataverse_subject:social-sciencessource · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
concepts[field].dataverse_subject:social-sciencessource · portal odissei nlconnector:portal_odissei_nl@1.0.0/subjects
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concepts[field].local:field:humanitiesmapping · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · portal odissei nlconnector:portal_odissei_nl@1.0.0/subjects
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