From Seeking to Sharing: Pathways of Environmental Risk Information on Social Media and the Roles of Outcome Expectations, Efficacy, and AI-Generated Content

This study explores the motivations driving Chinese consumers to share information about aquatic product safety risks related to radioactive wastewater discharge on social media, with a specific focus on the role of Artificial Intelligence Generated Content (AIGC) and prior information-seeking activities. The study examines key variables such as risk perception, outcome expectations, and the influence of AIGC literacy in shaping attitudes, social norms, and sharing efficacy. Data from 501 participants were analyzed using structural equation modeling. The findings indicate that risk evaluations and personal outcome expectations significantly motivate information sharing, while social expectations deter it. Additionally, AIGC literacy enhances both knowledge acquisition and sharing efficacy, while prior information seeking increases self-efficacy and risk perception, further fostering information sharing. These results provide critical insights into how environmental risk information is processed and disseminated on social media, emphasizing AIGC's role in influencing this process.