造谣
社会化媒体
可扩展性
计算机科学
人工智能
数据科学
互联网隐私
万维网
数据库
作者
Rongwei Tang,Yuming Fang,Jikai Sun,Leticia Bode,Emily K. Vraga
标识
DOI:10.1177/10776990251359660
摘要
This study investigates whether source expertise (expert vs. non-expert), use of artificial intelligence (AI; AI vs. non-AI), and the placement (debunking vs. prebunking) of a correction influence its effectiveness in reducing misperceptions and intentions to consume raw milk. Results of a pre-registered two-wave online experiment ( N 1 = 1,785, N 2 = 1,568) suggest that debunking consistently reduces misperceptions and behavioral intentions for at least 1 week, while prebunking was less effective. Expert corrections only outperform non-expert corrections in reducing misperceptions in wave 1. In general, AI cues do not significantly influence the effectiveness of a correction, offering both opportunities and challenges for organizations hoping to automate corrections.
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