A graph mining-based approach to analyze the dynamics of the Twitter community of COVID-19 misinformation disseminators

IF 4.1 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

ICT Express Pub Date : 2024-12-01 DOI:10.1016/j.icte.2024.10.006

Asma Ul Hussna , Risul Islam , Md Golam Rabiul Alam , Jia Uddin , Imran Ashraf , Md Abdus Samad

引用次数: 0

Abstract

This study explores the global problem of misinformation dissemination on social media, particularly Twitter, due to the COVID-19 pandemic. It identifies prominent disseminators, investigates the spread of false information and the ecosystem of disinformation spreaders, and assesses their online personalities. We track the interaction among fake news spreaders using the User–User Interaction Graph. The study reveals a rapidly growing population of disseminators, including professional spreaders, with over 3% dominating the others. The collaboration among fake news spreaders is high, highlighting the need for further research using publicly available online data to understand the community spreading malicious misinformation about COVID-19.

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来源期刊

ICT Express Multiple-

CiteScore

10.20

自引率

1.90%

发文量

167

审稿时长

35 weeks

期刊介绍： The ICT Express journal published by the Korean Institute of Communications and Information Sciences (KICS) is an international, peer-reviewed research publication covering all aspects of information and communication technology. The journal aims to publish research that helps advance the theoretical and practical understanding of ICT convergence, platform technologies, communication networks, and device technologies. The technology advancement in information and communication technology (ICT) sector enables portable devices to be always connected while supporting high data rate, resulting in the recent popularity of smartphones that have a considerable impact in economic and social development.