COVID vaccine misinformation: Toward an integrated approach for predicting the cascade of disinformation

The COVID-19 pandemic has highlighted the powerful influence of social media in shaping public opinion, particularly in spreading vaccine misinformation. This study investigates the dynamics of disinformation during the pandemic, focusing on its unprecedented scale and rapid proliferation, as well as its implications for political stability and public trust. It emphasizes the crucial role of Information Systems (IS) in addressing these challenges, utilizing advanced technologies such as algorithms, data analytics, and artificial intelligence for real-time tracking, analysis, and countermeasures against misinformation. The study employs a data analytics approach to analyze over 2 million vaccine-related tweets, classifying them as misinformation and reliable information. The findings reveal that misinformation spikes often coincide with periods of public uncertainty, while central nodes—highly connected social media users—play a key role in amplifying misinformation and reliable content. Despite the challenges, users tend to engage more with trustworthy information, offering opportunities to amplify factual content. By examining the influence of disinformation cascades and reviewing existing counter strategies, this study aims to illuminate the complexities of managing misinformation in today’s digital landscape. Furthermore, it underscores the need for an integrated, multidisciplinary approach that combines insights from Political Science and IS. This approach fosters media literacy, enhances transparency, and promotes trust in credible sources, thereby strengthening the resilience of information ecosystems against disinformation threats.