Social media misinformation sharing model spotlights repeat spreaders
Researchers say people who receive and repost false claims deserve more attention in efforts to slow misinformation online.
By Tom Brennan · Health & Medicine Correspondent
3 min read
A new study on social media misinformation sharing says the people who receive and repost false claims play a larger role than research has often recognized. The work matters because many anti-misinformation efforts focus on content creators or network design, while the study argues that user decisions help determine whether false information keeps circulating.
The research, published in the International Journal of Enterprise Network Management, was reported by Inderscience and credited to Sridevi Periaiya and co-authors. The authors examined evidence on how trust and belief shape users’ willingness to share misinformation, then paired that review with an unsupervised machine-learning analysis of user behavior.
From that work, the researchers developed a conceptual model intended to help users identify and respond to information that may be false. The model also points to behavior patterns linked with people who repeatedly spread misinformation, according to Inderscience.
Why do social media users keep sharing misinformation?
The study says misinformation research has given more attention to where false claims begin and how online networks are arranged than to the choices made by users who encounter those claims. The authors argue that those choices are central to understanding why misleading content is shared again and again.
Trust and personal belief are part of that process, according to the study. If users treat a post, account or message as credible, they may be more likely to pass it along, even when the information is inaccurate.
An unsupervised machine-learning analysis looks for patterns in data without relying on preset categories. In this case, the researchers used that approach to study user behavior and identify signals associated with repeated misinformation sharing.
Why the findings matter during disasters
The paper’s title focuses on misinformation sharing on social media during disasters, and Inderscience said the findings are especially relevant in emergencies. In those moments, social platforms can become a main source of updates for the public, increasing the stakes when misleading information spreads.
The researchers said the model could support several practical responses. Those include platform rules, media literacy programs, fact-checking efforts and moderation systems aimed at limiting the spread of misleading content.
The study also links those measures to public trust in online information. By paying closer attention to why users share questionable claims, the authors say institutions and platforms may be better able to reduce the circulation of false material.
What the model changes in misinformation research
The study does not shift attention away from people who create fake news. Instead, it broadens the frame to include the recipients who decide whether a post gains more reach.
That user-centered view treats misinformation as a process shaped by many decisions after a claim first appears online. According to the researchers, addressing those decisions is necessary for stronger responses to false information on social platforms.
The paper, “Decoding user behaviour: identifying user’s prone to misinformation sharing on social media during disasters,” was published in 2026 in the International Journal of Enterprise Network Management. The DOI listed for the study is 10.1504/ijenm.2026.154801.
This story draws on original reporting from Phys.org.