The COVID-19 pandemic not only gave us a global health crisis but also an infodemic, a term coined by the World Health Organization (WHO) to describe the overwhelming flood of information – both accurate and misleading – that inundated media channels. This information complicated the public understanding and response to the pandemic as people struggled to separate fact from fiction.
Researchers writing in the International Journal of Advanced Media and Communication suggest that a lot of attention has been paid to tracking and mitigating the spread of misinformation, but there has been less focus on the characteristics of the messages and sources that allow information to spread. This gap in the research literature has implications for how we might develop better strategies to counteract misinformation, particularly in times of crisis.
Ezgi Akar of the University of Wisconsin, USA, looked at social media updates, “Tweets” as they were once referred on the Twitter microblogging platform. Twitter has since been rebranded as “X”. At the time of the pandemic, Twitter had famously risen to the point where it was a powerful tool that could shape public discourse and at the time played an important role in the dissemination of information and social interaction, and, unfortunately, the spread of misinformation.
The research hoped to reveal how the content of a given update and the credibility of its source might contribute to its spread, or reach, across the social media platform, and beyond. The aim would be to see what factors might then be influenced to reduce the spread of false information, often referred to as fake news in the vernacular of the time
Akar’s model used three main theoretical frameworks: the Undeutsch hypothesis, which examines the credibility of statements; the four-factor theory, which looks at the various aspects that influence how believable a message is; and source credibility theory, which explores how the perceived reliability of a source affects the dissemination of information. He then used the model to analyse a dataset of tweets, both true and false to look for patterns.
The findings of the study reveal that while the content of an update – such as the use of extreme sentiments, external links, and media, such as photos and videos – affects the likelihood of the update being “liked” or shared “retweeted”, the credibility of the source has more effect on how widely the information spreads. This suggests that users will engage more with content from seemingly credible sources, even if the content itself is not particularly compelling.
An additional finding, that updates in all capital letters were more likely to be shared if they were providing true information. Usually, messages written in all capital letters are perceived as aggressive, akin to shouting, or naïve. But, “all caps” in the case of an important and urgent message seems to override typical user behaviour in certain situations.
Akar, E. (2024) ‘Unmasking an infodemic: what characteristics are fuelling misinformation on social media?’, Int. J. Advanced Media and Communication, Vol. 8, No. 1, pp.53–76.