Social media affordances and information abundance: Enabling fake news sharing during the COVID-19 health crisis

TLDR

The study models factors predicting fake news sharing during COVID‑19 using affordance and cognitive load theory and proposes intervention strategies to encourage skepticism toward social media information. Data from 385 Nigerian social media users were analyzed with Partial Least Squares to model fake news sharing predictors. The analysis revealed that perceived news‑find‑me, information overload, trust, status seeking, self‑expression, and information sharing all predicted fake news sharing, with news‑find‑me perception and information overload exerting the strongest influence.

Abstract

This study modelled factors that predict fake news sharing during the COVID-19 health crisis using the perspective of the affordance and cognitive load theory. Data were drawn from 385 social media users in Nigeria, and Partial Least Squares (PLS) was used to analyse the data. We found that news-find-me perception, information overload, trust in online information, status seeking, self-expression and information sharing predicted fake news sharing related to COVID-19 pandemic among social media users in Nigeria. Greater effects of news-find-me perception and information overload were found on fake news sharing behaviour as compared to trust in online information, status seeking, self-expression and information sharing. Theoretically, our study enriches the current literature by focusing on the affordances of social media and the abundance of online information in predicting fake news sharing behaviour among social media users, especially in Nigeria. Practically, we suggest intervention strategies which nudge people to be sceptical of the information they come across on social media.