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Vol. 5 No. 1 (2024)
2024 Edition

Articles

The Underlying Factors of How Information Sharing on Twitter Could Lead to Fake News during Times of Socio-Economic Crisis

Published 2024-11-24

  • Ron Evan del Rosario
    • ,
  • Chiehwen Ed Hsu

Ron Evan del Rosario
National Cheng Kung University, Taiwan

Chiehwen Ed Hsu
The University of Texas Health Science Center at Houston, USA

Abstract

This research explores the factors driving the spread of fake news on Twitter during socio-economic crises. In times of turmoil, Twitter becomes a key platform for information exchange, but its rapid, unregulated nature often fuels the dissemination of misinformation. The study aims to identify the primary drivers of fake news, focusing on user behavior, network dynamics, and content traits during socio-economic upheavals. A mixed-method approach was employed, incorporating both quantitative and qualitative analysis. Quantitatively, Twitter data related to major socio-economic events was analyzed to observe engagement patterns, retweet behavior, and the influence of key accounts. Qualitatively, content analysis of tweets was conducted to understand the narratives and sentiments behind misinformation trends. Results show that emotionally charged and sensational content spreads faster than factual information during crises. Amplification through retweets and likes significantly enhances the reach of unverified news. Users often engage in echo chambers, interacting mostly with like-minded individuals, reinforcing biases and limiting exposure to diverse perspectives. Influencers and automated bots also play a critical role in amplifying fake news. The research highlights the need for enhanced digital literacy and platform accountability to limit misinformation spread. It emphasizes the importance of content moderation, transparency in sources, and algorithmic adjustments to reduce the amplification of false information. These findings have implications for policymakers, social media companies, and users, stressing the necessity of creating a more resilient digital ecosystem capable of handling the pressures of socio-economic crises with accurate and reliable information.

Keywords

Fake News, Twitter, Socio-Economic Crisis, Misinformation, User Behavior, Network Dynamics

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