Developing a Stressor Strain Outcome Model That Predicts Fake News Sharing Behaviour on Social Media: The Mediating Role of Social Media Exhaustion

Abstract

Despite the growing corpus of knowledge on fake news sharing, nothing much is known about the relationship between the dissemination of fake news and social media exhaustion from an empirical standpoint. There is limited knowledge that exists to show if social media exhaustion could contribute to fake news-sharing behaviour. To address the gaps in the literature, this study created and evaluated a stressor strain outcome model that forecasts social media spread of fake news. It looked at the contributing elements of social media exhaustion before connecting it to disseminating fake news online. It also looked at how social media exhaustion functions as a mediator between its antecedents and fake news-sharing activity. Data was obtained from 1650 social media users using an online survey. Smart PLS structural equation modelling was used to examine the data. Our results, which drew on the stressor strain outcome model, demonstrated that, in the context of fake news-sharing behaviour, social media usage intensity is the most important predictor of social media exhaustion. Social media exhaustion was also predicted by information irrelevance, social media overload, the fear of missing out, and information overload. Also, social media tiredness predicts how people would share misleading news. Further research indicates that the link between information relevance, social overload, fear of missing out, information overload, and the dissemination of fake news is fully mediated by social media exhaustion. Conversely, it partially mediated the link between the frequency of using social media and the dissemination of false information. Our research provides recommendations to social media businesses and developers who wish to reduce concerns about social media tiredness and the spread of fake news.

Keywords:

• Antecedents of fake news
• fake news on social media
• fake news sharing behaviour
• fake news sharing
• social media exhaustion

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data used in the manuscript is confidential.

Additional information

Funding

The authors would like to acknowledge Agricultural University, School Prosperity and Development Philosophy and Social Science Foundation Project 2021sk17, Anhui Agricultural University, University Talent Stable Development Project, rc362002, Anhui Agricultural University, University Talent Stable Development project, rc362001 and China Postdoctoral Science Foundation, 2023M732089.

Notes on contributors

Luhui Hua

Luhui Hua, major in visual communication. Research interests include advertising communication, camera language, and digital multimedia. In February 2020, he obtained a doctorate degree in design from Dongseo University in Korea. He is a member of the Korean Design Association and the Korean Journal of Communication Design Research Association.

Yuan Jing

Yuan Jing is a lecturer/postgraduate tutor in Anhui Agricultural University. Main research interests include service design and landscape renewal, design thinking, community design, etc.

Xiaocui Sun

Xiaocui Sun is an associate researcher in School of Journalism and Communication, Shandong University. Main research interests include communication, economics of publishing media industry, digital publishing, copyright operation, etc.

Lujia Tian

Lujia Tian is a PhD student at the School of Journalism and Communication, Shandong University. Main research interests include journalism and communication, public opinion, news data statistics and analysis.

Oberiri Destiny Apuke

Oberiri Destiny Apuke is one of the best communication scholars in Nigeria (2020–2023), and part of the top 500 scholars in Nigeria according to SCOPUS Scival. He is a lecturer at the Department of Mass Communication, Taraba State University, Jalingo, Nigeria. He holds a PhD in Communication from the Universiti Sains Malaysia.