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

Authors :
Asma Ul Hussna
Risul Islam
Md Golam Rabiul Alam
Jia Uddin
Imran Ashraf
Md Abdus Samad
Source :
ICT Express, Vol 10, Iss 6, Pp 1280-1287 (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

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.

Details

Language :
English
ISSN :
24059595
Volume :
10
Issue :
6
Database :
Directory of Open Access Journals
Journal :
ICT Express
Publication Type :
Academic Journal
Accession number :
edsdoj.0f115c841cf4b6db6c635da1bf0b7d6
Document Type :
article
Full Text :
https://doi.org/10.1016/j.icte.2024.10.006