Are Mutated Misinformation More Contagious? A Case Study of COVID-19 Misinformation on Twitter

The spread of online misinformation has become a major global risk. Understanding how misinformation propagates on social media is vital. While prior studies suggest that the content factors, such as emotion and topic in texts, are closely related to the dissemination of misinformation, the effect of users’ commentary on misinformation during its spreading on social media has been long overlooked. In this paper, we identify the patterns of “misinformation mutation” which captures ways misinformation is commented and shared by social media users. Our study focus on misinformation originated from digital news outlets and shared on Twitter. Through an analysis of over 240 thousand tweets capturing how users share COVID-19 pandemic-related misinformation news over a five-month period, we study the prevalence and factors of the misinformation mutation. We examine the different kinds of mutation in terms of how the article was cited from the news source, and how the content was edited, compared with its original text, and test the relationship between misinformation’s mutation and its spread on Twitter. Our results indicate a positive relationship between information mutation and spreading outcome – and such a relationship is stronger for news articles shared from non-credible outlets than those from credible ones. This study provides the first quantitative evidence of how misinformation propagation may be exacerbated by users’ commentary. Our study contributes to the understanding of misinformation spreading on social media and has implications for countering misinformation.