Oberiri Destiny Apuke and Bahiyah Omar
This study developed a predictive model that established the user motivational factors that predict COVID-19 fake news sharing on social media.
Abstract
Purpose
This study developed a predictive model that established the user motivational factors that predict COVID-19 fake news sharing on social media.
Design/methodology/approach
The partial least squares structural equation modelling (PLS-SEM) was used for the analysis. Data were drawn from 152 Facebook and WhatsApp users in Nigeria to examine the research model formulated using the uses and gratification theory (UGT).
Findings
We found that altruism, instant news sharing, socialisation and self-promotion predicted fake news sharing related to COVID-19 pandemic among social media users in Nigeria. Specifically, altruism was the strongest predictor to fake news sharing behaviour related to COVID-19, followed by instant news sharing and socialisation. On the contrary, entertainment had no association with fake news sharing on COVID-19.
Practical implications
We suggest intervention strategies which nudge people to be sceptical of the information they come across on social media. We also recommend healthcare providers and the Nigerian government to provide relevant information on this current pandemic. That is, correct information should be shared widely to the public domain through various conventional and online media. This will lessen the spread of fake news on the concocted cure and prevention tips found online.
Originality/value
The salient contributions of this study are as follows: First, it brings to the fore that the desire for self-promotion is associated with fake news sharing on social media; second, it shifts the focus of studies on fake news from detection methods to sharing behaviour, which fuels the uncontrollable spread of falsehood; third, it expands the existing literature on misinformation sharing by demonstrating the user motivation that leads to fake news sharing using the UGT.