Weak ties, strong facts: how influencers amplify public health communication on X (formerly Twitter)

Abstract Purpose Social conformity theory emphasizes normative pressure as a drive of collective behavior. However, how these dynamics operate within weak-tie networks on social media remains underexplored. Platform-specific affordances such as X’s (formerly Twitter) network structures may reshape these dynamics in public health communication. Using COVID-19 vaccine-related discussions on X (formerly Twitter), this study investigates how networked influence reconfigures the informational and normative social influence during health crises. Design/methodology/approach Integrating computational methods, Latent Dirichlet Allocation (LDA) topic modeling, sentiment analysis, and network analysis, this study analyzes 5.5 million tweets about COVID-19 vaccines, collected worldwide via the Twitter Academic API between November 3, 2021, and May 5, 2022, to examine how user roles (influencers vs. general users), tie strength, and content type (factual vs. opinion-based) shape retweet patterns. Latent Dirichlet Allocation (LDA) was applied to uncover thematic structures in vaccine-related discussions, while TextBlob sentiment analysis quantified the subjectivity of tweets to differentiate factual from opinion-based content. Network analysis using iGraph identified influencers based on degree and betweenness centrality, enabling the classification of “authoritarians,” “accelerators,” and “connectors.” Findings Weak-tie connections drive information diffusion, with general users’ factual tweets shared more frequently than influencers’. Normative social influence from accelerators, connectors, or authoritarian accounts is constrained by X’s character limits and decentralized network structure. Opinion-based content, regardless of author status, receives fewer retweets, indicating users prioritize accuracy over subjective narratives. Practical implications Public health campaigns should prioritize concise, evidence-based messaging tailored to X’s decentralized networks. Leveraging general users as “fact-checking” nodes and minimizing opinion-laden content can amplify reach. Strategies to counter misinformation must account for platform-specific limitations on normative influence. Social implications The findings underscore how digital platforms democratize health communication by empowering non-expert users to shape discourse, while challenging top-down public health messaging. This duality highlights opportunities to bridge information gaps in underserved communities through weak-tie networks. Originality/value The first study to dissect social conformity mechanisms on X through a tripartite computational lens, revealing how platform affordances disrupt traditional hierarchies of influence. It redefines “influencer” roles in public health contexts, demonstrating that weak ties and factual content supersede normative pressure in driving engagement.