Information Characteristics and Social Media Information Sharing: Insights from Elaboration Likelihood Model (ELM) for Misinformation Mitigation

The rapid dissemination of information on social media has many positives but has also raised significant concerns regarding misinformation, making it crucial to understand the factors driving information-sharing behavior. This study employs the Elaboration Likelihood Model (ELM) with its dual processing pathways (central and peripheral route processing) to identify key information characteristics influencing information-sharing behavior on social media. Through Reflexive Thematic Analysis (RTA) of 92 viral tweets from three Malaysian news channels between January and October 2024, five key themes emerged: Social Interest, Political Interest, Visual Appeal, Credible Sources, and Emotional Appeal. Illustrative case studies of viral Malaysian tweets were analyzed, revealing how different information characteristics trigger varying cognitive processing routes. Our findings indicate that Social Interest and Political Interest align with central route processing, require deeper cognitive engagement. Conversely, Visual Appeal, Credible Sources, and Emotional Appeal follow the peripheral route processing, relying on heuristic cues. Importantly, many viral tweets engage mixed processing, highlighting the need for hybrid interventions. Building on these insights, the study offers practical guidance for stakeholders: policymakers can enforce regulations and promote awareness, platforms can add credibility markers and prioritize trusted sources, educators can teach media literacy, and users can adopt a “pause-and-verify” approach. Collectively, these efforts can help create a digital ecosystem that balances user engagement with accuracy in online information sharing.