Abstract
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.
Data availability statement
This study data can be obtained: https://data.mendeley.com/datasets/mjy5kssj22/1
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Funding
Notes on contributors
Yi Wan
Yi Wan is with the School of Journalism and Communication, at Central China Normal University.
Oberiri Destiny Apuke
Oberiri Destiny Apuke is one of the best communication scholars in Nigeria (2020–2023), and part of top 500 scholars in Nigeria according to SCOPUS Scival. He is a lecturer at Department of Mass Communication, Taraba State University, Jalingo, Nigeria. He holds PhD in Communication from the Universiti Sains Malaysia.