Affiliation:
1. School of Communication, Universiti Sains Malaysia, Pulau Penang, Malaysia
2. Department of Mass Communication, Taraba State University, Jalingo, Nigeria
Abstract
Abstract
We proposed a conceptual model combining three theories: uses and gratification theory, social networking sites (SNS) dependency theory and social impact theory to understand the factors that predict fake news sharing related to COVID-19. We also tested the moderating role of fake news knowledge in reducing the tendency to share fake news. Data were drawn from social media users (n = 650) in Nigeria, and partial least squares was used to analyse the data. Our results suggest that tie strength was the strongest predictor of fake news sharing related to COVID-19 pandemic. We also found perceived herd, SNS dependency, information-seeking and parasocial interaction to be significant predictors of fake news sharing. The effect of status-seeking on fake news sharing, however, was not significant. Our results also established that fake news knowledge significantly moderated the effect of perceived herd, SNS dependency, information-seeking, parasocial interaction on fake news sharing related to COVID-19. However, tie strength and status-seeking effects were not moderated.
Funder
Universiti Sains Malaysia
Research University
Publisher
Oxford University Press (OUP)
Subject
Public Health, Environmental and Occupational Health,Education
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