Computer Science > Human-Computer Interaction
[Submitted on 21 Oct 2025
]
Title: Examining the Impact of Label Detail and Content Stakes on User Perceptions of AI-Generated Images on Social Media
Title: 考察标签详细程度和内容重要性对用户在社交媒体上对AI生成图像看法的影响
Abstract: AI-generated images are increasingly prevalent on social media, raising concerns about trust and authenticity. This study investigates how different levels of label detail (basic, moderate, maximum) and content stakes (high vs. low) influence user engagement with and perceptions of AI-generated images through a within-subjects experimental study with 105 participants. Our findings reveal that increasing label detail enhances user perceptions of label transparency but does not affect user engagement. However, content stakes significantly impact user engagement and perceptions, with users demonstrating higher engagement and trust in low-stakes images. These results suggest that social media platforms can adopt detailed labels to improve transparency without compromising user engagement, offering insights for effective labeling strategies for AI-generated content.
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