Towards Healthy Engagement with Online Debates An Investigation of Debate Summaries and Personalized Persuasive Suggestions

Alisa Rieger, Qurat Ul Ain Shaheen, Carles Sierra, Mariet Theune, Nava Tintarev

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)
32 Downloads (Pure)

Abstract

Online debates allow for large-scale participation by users with different opinions, values, and backgrounds. While this is beneficial for democratic discourse, such debates often tend to be cognitively demanding due to the high quantity and low quality of non-expert contributions. High cognitive demand, in turn, can make users vulnerable to cognitive biases such as confirmation bias, hindering well-informed attitude forming. To facilitate interaction with online debates, counter confirmation bias, and nudge users towards engagement with online debate, we propose (1) summaries of the arguments made in the debate and (2) personalized persuasive suggestions to motivate users to engage with the debate summaries. We tested the effect of four different versions of the debate display (without summary, with summary and neutral suggestion, with summary and personalized persuasive suggestion, with summary and random persuasive suggestion) on participants' attitude-opposing argument recall with a preregistered user study (N = 212). The user study results show no evidence for an effect of either the summary or the personalized persuasive suggestions on participants' attitude-opposing argument recall. Further, we did not observe confirmation bias in participants' argument recall, regardless of the debate display. We discuss these observations in light of additionally collected exploratory data, which provides some pointers towards possible causes for the lack of significant findings. Motivated by these considerations, we propose two new hypotheses and ideas for improving relevant properties of the study design for follow-up studies.

Original languageEnglish
Title of host publicationUMAP2022 - Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
PublisherAssociation for Computing Machinery
Pages192-199
Number of pages8
ISBN (Electronic)9781450392327
DOIs
Publication statusPublished - 4 Jul 2022
Event30th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2022 - Virtual, Online, Spain
Duration: 4 Jul 20227 Jul 2022
Conference number: 30

Conference

Conference30th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2022
Abbreviated titleUMAP 2022
Country/TerritorySpain
CityVirtual, Online
Period4/07/227/07/22

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