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AI content labeling and user engagement on social media: The role of AI level, content type, and disclosure timing

Freya Seeger et al.

Electronic Markets2026https://doi.org/10.1007/s12525-026-00883-2article
AJG 2ABDC A
Weight
0.50

Abstract

The rapid adoption of generative AI by content creators, coupled with the emergence of legal requirements for labeling AI-generated content, raises important questions about the implications of AI on user engagement on social media platforms. We examine how the level of AI involvement (human-created, AI-enhanced, or AI-generated), content type (emotional or rational), and disclosure timing (early or late) impact user engagement through two online experiments (study 1: n = 325; study 2: n = 371) conducted via the crowdsourcing platform Prolific. Participants (mean age = 35 years; 55% female) were asked to view Instagram profiles containing visual content labeled as human-created, AI-enhanced, or AI-generated. The results show that labeling content as AI-generated or AI-enhanced reduced both affective and behavioral engagement compared to human-created content, particularly for emotional content. Late disclosure of AI involvement improved affective engagement for AI-enhanced content, but not for AI-generated content. These findings deepen the understanding of algorithmic aversion in the context of generative AI and offer practical guidance for creators and platforms navigating the tension between transparency and engagement in an increasingly AI-mediated content ecosystem.

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https://doi.org/https://doi.org/10.1007/s12525-026-00883-2

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@article{freya2026,
  title        = {{AI content labeling and user engagement on social media: The role of AI level, content type, and disclosure timing}},
  author       = {Freya Seeger et al.},
  journal      = {Electronic Markets},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s12525-026-00883-2},
}

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AI content labeling and user engagement on social media: The role of AI level, content type, and disclosure timing

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.