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

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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Publication Details

Journal
ICT Express
Published
2024-11-05
DOI
https://doi.org/10.1016/j.icte.2024.10.006
Citations
1
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
1.13
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article

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

Asma Ul Hussna, Jia Uddin, Risul Islam, Md. Golam Rabiul Alam et al.
1 citations
ICT Express
Misinformation and Its Impacts
1.13
article

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

Asma Ul Hussna, Jia Uddin, Risul Islam, Md. Golam Rabiul Alam, Imran Ashraf, Md Abdus Samad
article en
1 citations

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.

ICT ExpressVol. 10(6)
Palo Alto Networks (United States) (US), BRAC University (BD), Yeungnam University (KR), Woosong University (KR)
Reduced inequalities
Openalex Percentile: Top 15%
Misinformation and Its Impacts
1.13
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