Paper Type
Short
Paper Number
PACIS2025-1106
Description
Companies are increasingly using AI-generated content (AIGC) in social media marketing, including visually appealing AI-generated advertisement images that resonate with their audience. However, concerns about its authenticity, which may alienate audiences, have prompted social media platforms to enhance AIGC disclosure by adopting automated detection algorithms. While prior research primarily focuses on the disclosure of interactive AI-enabled applications, it remains underexplored how users respond to non-interactive AIGC. Motivated by these gaps, this study aims to investigate how algorithm-based disclosure of AIGC influences users’ social and commercial behaviors on social media platforms. To achieve this, we develop a research model based on the Stimulus-Organism-Response framework and related literature on AI disclosure and social media marketing. We propose that users’ responses vary across different product claims. A pilot experimental study was conducted to test the hypotheses. This study contributes to the related literature and provides suggestions for marketers to leverage AIGC effectively.
Recommended Citation
Zhou, Ya; She, Junyi; and Luo, Cheng, "What You Claim Matters: Understanding Algorithm-based Disclosure of AI-Generated Content on Social Media Platforms" (2025). PACIS 2025 Proceedings. 10.
https://aisel.aisnet.org/pacis2025/sm_digcollab/sm_digcollab/10
What You Claim Matters: Understanding Algorithm-based Disclosure of AI-Generated Content on Social Media Platforms
Companies are increasingly using AI-generated content (AIGC) in social media marketing, including visually appealing AI-generated advertisement images that resonate with their audience. However, concerns about its authenticity, which may alienate audiences, have prompted social media platforms to enhance AIGC disclosure by adopting automated detection algorithms. While prior research primarily focuses on the disclosure of interactive AI-enabled applications, it remains underexplored how users respond to non-interactive AIGC. Motivated by these gaps, this study aims to investigate how algorithm-based disclosure of AIGC influences users’ social and commercial behaviors on social media platforms. To achieve this, we develop a research model based on the Stimulus-Organism-Response framework and related literature on AI disclosure and social media marketing. We propose that users’ responses vary across different product claims. A pilot experimental study was conducted to test the hypotheses. This study contributes to the related literature and provides suggestions for marketers to leverage AIGC effectively.
Comments
Social