Investigating Factors Influencing The Intention of Social Media Users to Use Generative AI for Health Misinformation Fact Checking with an Extended Technology Acceptance Model(TAM)

This study expands upon Fred Davis' Technology Acceptance Model (TAM) by incorporating two external variables, perceived enjoyment and self-efficacy, to investigate the factors influencing social media users' adoption of generative AI for health misinformation fact-checking. A survey was conducted to 515 Chinese social media users, focusing on their perceptions concerning the application of generative AI in fact-checking. Notably, 79.8% of the survey participants(n=411)reported having utilized generative AI for fact-checking at least once before. Statistical analysis revealed positive correlations among perceived usefulness, perceived ease of use, perceived enjoyment, and self-efficacy in relation to users' expectations of generative AI’ effectiveness in fact-checking. This study support the notion that TAM serves as a viable framework for predicting social media users' acceptance of generative AI technologies. Furthermore, the implications of this research could provide valuable insights for software developers and researchers, enhancing their comprehension of the determinants that affect user acceptance of emerging technologies. The study also offers suggestions for future research directions in this domain.