What makes a rumour on social media stick? A mathematical model offers some clues

Why does some unverified information on social media continue to spread, while other information gradually disappears? An international team of scientists, including researchers from IT4Innovationsat VŠB-TUO, has developed a mathematical model that examines how rumours and debunking information spread and how other factors influence this process. The study, supported by REFRESH, has been published in Scientific Reports.

To ensure the model closely reflects real-world social media behaviour, the researchers divided users into four groups: those who are encountering the information for the first time, active spreaders of the information, users or organisations seeking to refute it, and those who are no longer interested in its further dissemination. The model describes how users may transition between these groups after encountering a rumour.

The resulting model also links three factors that previous approaches have often studied in isolation: long-term memory, response delay, and random changes in user behaviour. It therefore takes into account that our current response also depends on what we have encountered previously, that verifying or responding to information takes some time, and that people’s behaviour on the internet is not entirely predictable. It is precisely the integration of these three factors into a single model that is one of the study’s main contributions.

When a rumour persists and when it dies down

One of the key parameters of the model is the reproduction number R₁, which, much like in infectious disease spreading models, indicates whether a rumour can persist in the system over the long term. If its value is less than one, the spread gradually dies out. If it exceeds this threshold, the rumour may continue to persist.

The researchers also investigated which parameters influence a rumour’s capacity to spread over the long term. The results showed that a higher rate of spread and a larger proportion of users who believe the rumour and start spreading it further increase the reproduction number R₁. Conversely, blocking or reporting those who spread it reduces this value. Separate simulations also showed that time plays a significant role: the longer it takes to verify the information or to intervene to curb its spread, the more the rumour’s subsequent development may change, and the more difficult it becomes to limit its spread.

Practical applications

The model can serve as a virtual environment for testing various scenarios. “For example, it allows us to examine how the situation changes if there is a faster response to unverified information or if its further spread is curbed more effectively. Such simulations can help us better understand which factors to focus on when countering misinformation and rumours, and when intervention is most effective,” says Marek Lampart from IT4Innovations.

According to him, however, this is not a tool that predicts the fate of a specific social media post. “It is a mathematical model that helps to isolate individual factors, test their combinations and better understand the mechanisms that determine whether a rumour will persist or gradually fade away,” he added.

Source: IT4Innovations