Three Years of Pandemic and Misinformation: Longitudinal Characterization of False Information Regarding COVID-19 in Chile

Abstract

Health-related misinformation gained particular relevance during the COVID-19 outbreak, a context that generated a large amount of fake news. This study proposes an explanatory theory regarding the frequency and content of pandemic-related fake news. A total of 240 fake news items disseminated in Chile between 2020 and 2022 were analyzed, collected from the platforms Fast Check and Mala Espina. The information was coded using two complementary schemes: (i) a general classification of the domains of fake news and (ii) an emergent coding specific to false information related to the pandemic. According to the first scheme, fake news were mainly related to science and health (69.6%), politics and management (19.6%), and other topics (10.8%). According to the second scheme, they were associated with the nature of the pandemic (23.8%), preventive measures (60.8%), and alternative narratives (15.4%). The highest frequency of fake news was recorded in 2021 (43.3%). The study proposes a theoretical model that explains the dynamics of detecting different types of fake news throughout the pandemic, suggesting that their creation may be related to the need to reduce uncertainty in health-crisis contexts.