User Perceptions of AI-Based Comment Filtering Technology

被引:4
|
作者
Oh, Yu Won [1 ]
Park, Chong Hyun [2 ,3 ]
机构
[1] Myongji Univ, Dept Digital Media, Seoul, South Korea
[2] Sungkyunkwan Univ, Sch Business, Seoul, South Korea
[3] Sungkyunkwan Univ, Sch Business, 25-2 Sungkyunkwan-ro, Seoul 03063, South Korea
关键词
AI moderation; comment filtering; comments section; use intention; user perception; BUILD THEORY; NEWS; ONLINE; MACHINE; AUTHORSHIP; MEDIA; MODERATION; DEMOCRACY; OPINION; BIAS;
D O I
10.1177/00027642231174331
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
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.
引用
收藏
页码:1308 / 1324
页数:17
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