mlsanityData to 14 Oct 2026

Examining the Impact of Label Detail and Content Stakes on User Perceptions of AI-Generated Images on Social Media

arXiv 2510.19024 ↗First posted 21 Oct 2025cs.HCcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Oct 2025.

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Citing papers per year: 2025: 1; 2026: 2.

3 papers.