可靠性
来源可信度
新闻
感知
心理学
自然(考古学)
舆论
社会心理学
自然实验
假新闻
内容分析
广告
新闻媒体
生成语法
数据科学
公共关系
政治学
互联网隐私
计算机科学
应用心理学
数据源
生成模型
技术新闻
描述性统计
作者
Hye Min Kim,Eun-Ju Lee,Jin Won Park,Nathan Walter
出处
期刊:Cyberpsychology, Behavior, and Social Networking
[Mary Ann Liebert, Inc.]
日期:2026-04-07
卷期号:29 (5): 281-288
被引量:6
标识
DOI:10.1177/21522715261439452
摘要
As generative artificial intelligence (AI) becomes increasingly integrated into news production, concerns about the credibility of synthetic news content are intensifying. While some studies report that audiences find AI-generated news less credible than human-written content, others reveal mixed or even reversed findings. This meta-analysis synthesizes findings across 31 studies (41 effect sizes) to assess how the source label (AI vs. human) influences news users' evaluations of source credibility and message credibility. Results show a small but statistically significant penalty for AI-labeled (vs. human-labeled) news on both credibility measures. To better understand variability across studies, we put forth three moderators: (1) the value-ladenness of the topic, (2) participants' source orientation, and (3) actual authorship of the text. Although the first two moderators showed descriptive trends consistent with expectations, only the third reached statistical significance, with effects being more pronounced when the news articles were actually written by human only (vs. AI). These findings contribute to ongoing debates about the role of automation in journalism by clarifying when and why audiences mind the source.
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