The Role of AI-Generated Content Transparency in Shaping Public Trust and Information Acceptance on Social Media Platforms

Abstract

The increasing prevalence of AI-generated content on social media platforms has raised concerns regarding information credibility, authenticity, and users’ ability to evaluate digital information. As artificial intelligence becomes increasingly integrated into online communication, transparency regarding AI involvement in content creation has emerged as an important mechanism for reducing uncertainty and promoting trust. This study aims to examine the role of AI-generated content transparency in shaping public trust and information acceptance on social media platforms. A quantitative research approach was employed using a survey method. Data were collected from 250 active social media users who had prior experience interacting with AI-generated content. The proposed research model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the direct and indirect relationships among AI-generated content transparency, public trust, and information acceptance. The results indicate that AI-generated content transparency has a significant positive effect on public trust and information acceptance. Public trust also exerts a significant positive influence on information acceptance. Furthermore, public trust partially mediates the relationship between AI-generated content transparency and information acceptance, indicating that transparency enhances information acceptance both directly and indirectly through increased trust. The findings highlight the importance of transparent disclosure mechanisms in AI-mediated communication environments. By strengthening public trust and facilitating information acceptance, transparency can contribute to the development of a more accountable, credible, and trustworthy digital information ecosystem. The study further contributes to the literature by integrating transparency, trust, and information acceptance into a unified framework for understanding user responses to AI-generated content on social media platforms.