Modelling the Association Between Social Media Flow Experience and Fake News Sharing: Testing the Mediating Role of Social Media Flow Experience and the Moderating Role of Social Media Scepticism

This study developed a model that predicts fake news sharing behaviour on social media using the technology acceptance model (TAM) and flow theory. We collected survey responses from an online survey panel administered by a reputable market research firm, Qualtrics Inc. The recruitment of the participants was via Qualtrics's own pool of participants. Data analysis was done using Smart PLS structural equation modelling. We found FOMO to be the most significant factor that predicts social media flow experience. This is followed by enjoyment, perceived ease of use, perceived usefulness, and pass time, respectively. It is also our findings that social media flow experience predicts fake news sharing behaviour. We also found that social media flow experience fully mediates the relationship between enjoyment, FOMO, pass time, perceived utility, perceived ease of use and fake news sharing. Furthermore, the relationship between social media flow experience and fake news sharing is moderated by social media scepticism in such a way that this relationship is more pronounced among those with low social media scepticism. Our study contributes to theory and practice.