research-article

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Russo-Ukrainian War: Prediction and explanation of Twitter suspension

Authors:

Alexander Shevtsov,

Despoina Antonakaki,

Ioannis Lamprou,

Ioannis Kontogiorgakis,

Polyvios Pratikakis,

Sotiris IoannidisAuthors Info & Claims

ASONAM '23: Proceedings of the International Conference on Advances in Social Networks Analysis and Mining

Pages 348 - 355

https://doi.org/10.1145/3625007.3627317

Published: 15 March 2024 Publication History

Abstract

On 24 February 2022, Russia invaded Ukraine, starting what is now known as the Russo-Ukrainian War, initiating an online discourse on SNs. Twitter one of the most popular SNs, with an open and democratic character, enables a transparent discussion among its large user base. Unfortunately, this often leads to Twitter's policy violations, propaganda, abusive actions, civil integrity violations, and consequently to user accounts' suspension and deletion. This study focuses on the Twitter suspension mechanism and the analysis of shared content and features leading to an accurate machine-learning suspension prediction. Toward this goal, we have obtained a dataset containing 107.7M tweets, originating from 9.8 million users, using Twitter API. We extract the categories of shared content of the suspended accounts and explain their characteristics, through the extraction of text embeddings in junction with cosine similarity clustering. Our results reveal scam campaigns taking advantage of trending topics regarding the Russia-Ukrainian conflict for Bitcoin and Ethereum fraud, spam, and advertisement campaigns. Additionally, we apply a ML methodology including a SHapley Additive explainability model to understand and explain how user accounts get suspended.

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Cited By

Lamprou IShevtsov AAntonakaki DPratikakis PIoannidis S(2025)Exploring Crisis-Driven Social Media Patterns: A Twitter Dataset of Usage During the Russo-Ukrainian WarSocial Networks Analysis and Mining10.1007/978-3-031-78541-2_5(70-85)Online publication date: 24-Jan-2025
https://doi.org/10.1007/978-3-031-78541-2_5
Shah MAbuaieta AAlmazrouei S(2024)Safeguarding Online Communications using DistilRoBERTa for Detection of Terrorism and Offensive ChatsJournal of Information Security and Cybercrimes Research10.26735/VNVR27917:1(93-107)Online publication date: 29-Jun-2024
https://doi.org/10.26735/VNVR2791

Index Terms

Russo-Ukrainian War: Prediction and explanation of Twitter suspension

Index terms have been assigned to the content through auto-classification.

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Published In

cover image ACM Conferences

ASONAM '23: Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

November 2023

835 pages

ISBN:9798400704093

DOI:10.1145/3625007

Chair:
Jon Rokne,
Program Chair:
Dong Wang

Copyright © 2023 Owner/Author(s).

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 15 March 2024

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ASONAM '23

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ASONAM '23: International Conference on Advances in Social Networks Analysis and Mining

November 6 - 9, 2023

Kusadasi, Turkiye

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ASONAM '23 Paper Acceptance Rate 53 of 145 submissions, 37%;

Overall Acceptance Rate 116 of 549 submissions, 21%

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Cited By

Lamprou IShevtsov AAntonakaki DPratikakis PIoannidis S(2025)Exploring Crisis-Driven Social Media Patterns: A Twitter Dataset of Usage During the Russo-Ukrainian WarSocial Networks Analysis and Mining10.1007/978-3-031-78541-2_5(70-85)Online publication date: 24-Jan-2025
https://doi.org/10.1007/978-3-031-78541-2_5
Shah MAbuaieta AAlmazrouei S(2024)Safeguarding Online Communications using DistilRoBERTa for Detection of Terrorism and Offensive ChatsJournal of Information Security and Cybercrimes Research10.26735/VNVR27917:1(93-107)Online publication date: 29-Jun-2024
https://doi.org/10.26735/VNVR2791

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