Modelling the Information Abundance Factors That Predict Fake News Sharing Behaviour of Social Media Users: Testing the Moderating Role of Resilience

In: Journal of Asian and African studies: JAAS

Abstract

Fake news is widely shared on social media platforms, and while the literature is expanding, study into the motivations behind such sharing has not yet provided many answers. Drawing from the cognitive load theory and literature on resilience, we developed and tested a research model hypothesising why people share fake news. We also tested the moderating role of social media resilience. We obtained data from 1068 social media users in Nigeria using a chain referral technique with an online questionnaire as the instrument for data collection. Our findings suggest that information overload and information strain strongly predict fake news sharing. Social overload and irrelevant information also contributed to fake news sharing behaviour. Furthermore, resilience moderated and weakened the effect of information strain, information overload, irrelevant information, and social overload on fake news sharing in such a way that this effect is more pronounced among those with low resilience. This indicates that those with low resilience tend to share fake news when confronted with much information on social media. The study concluded with some theoretical and practical implications.