User Perceptions of AI-Based Comment Filtering Technology

As artificial intelligence (AI)-powered technology enables the efficient processing of large volumes of comments, more companies, including news publications, are experimenting with and adopting AI moderation to manage their commenting platforms. However, the resulting user experiences have been lar...

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Bibliographic Details
Published in:The American behavioral scientist (Beverly Hills) 2024-09, Vol.68 (10), p.1308-1324
Main Authors: Oh, Yu Won, Park, Chong Hyun
Format: Article
Language:English
Subjects:
Americans
Artificial intelligence
business enterprises
Comments
Credibility
filters
Moderation
Negative emotions
Perceptions
Priming
scientists
Technology
volume
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Summary:As artificial intelligence (AI)-powered technology enables the efficient processing of large volumes of comments, more companies, including news publications, are experimenting with and adopting AI moderation to manage their commenting platforms. However, the resulting user experiences have been largely underexplored in relation to these technical advances in comments section management. This study used an experiment to examine the impact of AI filters on individuals’ perceptions about comments sections (i.e., bias, credibility, positive and negative affect, and use intention). The findings indicate that AI moderation had statistically significant impacts on perceived credibility and use intention. Beyond the main effects, priming with a deceptive comment issue moderated the impacts of comment filtering on user perceptions as well.
ISSN:0002-7642
1552-3381
1552-3381
DOI:10.1177/00027642231174331