Limited individual attention and information overload could explain why low quality information, such as fake news and hoaxes, spreads virally on social media, concludes a paper published online this week in Nature Human Behaviour. Understanding the reasons why fake news goes viral is crucial to developing new tools for controlling the spread of false information.
Previous research has shown that a combination of social network structure and finite attention are sufficient for viral memes to emerge. Although it might seem logical that information quality plays a role in determining which information goes viral, the spread of misinformation of fake news on social media sites suggests otherwise.
Diego Fregolente Mendes de Oliveira and colleagues demonstrate that behavioural limitations reduce the ability of social media platforms to discriminate between low and high quality information. In this study, the authors develop a meme (transmissible piece of information or idea) diffusion model to explore how information load (average number of memes received by an individual per unit of time) and individual attention interact with the quality of a meme to affect its popularity. They find that it is theoretically possible to have a social media marketplace where a good trade-off between quality and diversity of information is achieved. However, when the model is calibrated with real-world measures of information load and attention derived from Twitter and Tumblr, they find that high and low quality information are shared at similar rates.
The authors conclude that one way to increase the discriminative power of social media and to prevent the spread of misinformation is to curb the use of bots that flood social media with low quality information.