Fake News Diffusion: A Process-Based Approach.

The dissemination of fake news intensified during the COVID-19 pandemic. Thus, in this paper we propose a process-based model grounded on the diffusion of innovations theory to investigate how fake news was shared via social media. Accordingly, data was categorized according to the taxonomy of process, namely: input, output, players and activities. We found that individual decision-making traits, fake news perceived features and communication channel attributes are determinants of a personal attitude vis-à-vis a received fake news. The attitude then leads to the decision of whether or not to believe in the fake news, while confirmation conveys to the spread of same. In this way, social media, mediated by the power of algorithms and echo chambers, increase the chance of spreading misinformation. [ABSTRACT FROM AUTHOR]