假新闻
感知
计算机科学
互联网隐私
计算机安全
心理学
神经科学
作者
Kim Fröhnel,Bennet Santelmann,Rüdiger Zarnekow
出处
期刊:Proceedings of the ... Annual Hawaii International Conference on System Sciences
日期:2025-01-01
标识
DOI:10.24251/hicss.2025.505
摘要
The importance of online reviews for consumers' decision-making engages fraudsters to game the review system by writing or buying fake reviews. Fake reviews are a main threat to consumers since they are hardly distinguishable from genuine human-made reviews. Moreover, advances in generative AI like ChatGPT foster the simple creation of persuasive text, such as high-quality fake reviews. While prior studies primarily focused on automatic fake review detection, little is known about how consumers react to AI-generated fake reviews. Based on a quantitative-qualitative study with 151 consumers (906 review classifications), we found that humans cannot reliably distinguish between genuine and AI-generated fake reviews (accuracy= 53.2%). They are especially worse at detecting negative AI-generated fake reviews. Our findings extend prior research by examining consumers' ability to detect AI-generated fake reviews, identifying a set of cues they use for review classification, and investigating the cues' effectiveness for detection. Further, we derive practical implications.
科研通智能强力驱动
Strongly Powered by AbleSci AI