An empirical approach to understanding users' fake news identification on social media

Abstract

Purpose

During the past few years, the rise in social media use for information purposes in the absence of adequate control mechanisms has led to growing concerns about the reliability of the information in circulation and increased the presence of fake news. While this topic has recently gained researchers' attention, very little is known about users' fake news identification behavior. Hence, the purpose of this study is to understand the factors that contribute to individuals' identification of fake news on social media.

Design/methodology/approach

This study employs a quantitative approach and proposes a behavioral model that explores the factors influencing users' identification of fake news on social media. It relies on data collected from a sample of 211 social media users which is tested using SEM.

Findings

The findings show that expertise in social media use and verification behavior have a positive impact on fake news identification, while trust in social media as an information channel decreases this identification behavior. Furthermore, results establish the mediating role of social media information trust and verification behavior.

Originality/value

The present study enhances our understanding of social media users' fake news identification by presenting a behavioral model. It is one of the few that focuses on the individual and argues that by identifying the factors that reinforce users' fake news identification behavior on social media, this type of misinformation can be reduced. It offers several theoretical and practical contributions.

Citation

Aoun Barakat, K., Dabbous, A. and Tarhini, A. (2021), "An empirical approach to understanding users' fake news identification on social media", Online Information Review, Vol. 45 No. 6, pp. 1080-1096. https://doi.org/10.1108/OIR-08-2020-0333