Mapping misinformation gatekeepers in non-western contexts: A computational network analysis of fake news on X (Twitter) using Gephi

This study investigates the gatekeeping of fake news dissemination on X (formerly Twitter) in non-Western contexts (data from India and Bangladesh), identifying influential actors in the online fake news ecosystem. Grounded in cascade theory, the research applies network analysis to examine how fake news spreads in these countries, where political and religious misinformation is prevalent. Using data from 10,001 X posts from April 2024 that reference the term ''fake news,'' the study analyzes key accounts based on betweenness centrality, eigenvector centrality, and modularity class. Employing both computational methods and qualitative text analysis, the study visualizes network structures, relationships, and topic trends. Findings reveal that individual personal accounts, rather than large institutional or media accounts, dominate fake news conversations. While larger accounts have broader reach, they are not as influential in controlling information flow. The primary topics driving fake news discussions are political and religious, with a clear focus on the upcoming elections in both countries. This study contributes to both theory and practice by offering insights into the misinformation landscape in non-Western contexts and suggesting future research directions, including surveys and platform-specific studies. Additionally, it provides practical implications for policymakers seeking to combat misinformation through enhanced digital literacy and regulatory frameworks.

Abstract licence: CC BY-NC

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