An Empirical Analysis of Health-Related Campaigns on Twitter Arabic Hashtags

TY - GEN

T1 - An Empirical Analysis of Health-Related Campaigns on Twitter Arabic Hashtags

AU - Imam, Niddal H.

AU - Vassilakis, Vassilios G.

AU - Kolovos, Dimitris

N1 - Publisher Copyright: © 2022 IEEE.

PY - 2022/3/23

Y1 - 2022/3/23

N2 - Twitter trending hashtags are a primary feature, where users regularly visit to get news or chat with each other. However, this valuable feature has been abused by malicious campaigns that use Twitter hashtags to disseminate religious hatred, promote terrorist propaganda, distribute fake financial news, and spread healthcare rumours. In recent years, some health-related campaigns flooded Arabic trending hashtags in Twitter. These campaigns not only irritate users, but they also distribute malicious content. In this paper, a comprehensive empirical analysis of the ongoing health-related campaigns on Twitter Arabic hashtags is presented. After collecting and an-notating tweets posted by these campaigns, we qualitatively analyzed the characteristics and behaviours of these tweets. We seek to find out what makes some of the tweets posted by these campaigns difficult to detect. Two main findings were identified: (1) these campaigns exhibit some spamming activities, such as using bots and trolls, (2) they use unique hijacked accounts as adversarial examples to obfuscate detection. This study is the first to qualitatively analyze health-related campaigns on Twitter Arabic hashtags from security point of view. Our findings suggest that some of the tweets posted by these campaigns need to be treated as adversarial examples that have not only been crafted to evade detection but also to undermine the deployed detection system.

AB - Twitter trending hashtags are a primary feature, where users regularly visit to get news or chat with each other. However, this valuable feature has been abused by malicious campaigns that use Twitter hashtags to disseminate religious hatred, promote terrorist propaganda, distribute fake financial news, and spread healthcare rumours. In recent years, some health-related campaigns flooded Arabic trending hashtags in Twitter. These campaigns not only irritate users, but they also distribute malicious content. In this paper, a comprehensive empirical analysis of the ongoing health-related campaigns on Twitter Arabic hashtags is presented. After collecting and an-notating tweets posted by these campaigns, we qualitatively analyzed the characteristics and behaviours of these tweets. We seek to find out what makes some of the tweets posted by these campaigns difficult to detect. Two main findings were identified: (1) these campaigns exhibit some spamming activities, such as using bots and trolls, (2) they use unique hijacked accounts as adversarial examples to obfuscate detection. This study is the first to qualitatively analyze health-related campaigns on Twitter Arabic hashtags from security point of view. Our findings suggest that some of the tweets posted by these campaigns need to be treated as adversarial examples that have not only been crafted to evade detection but also to undermine the deployed detection system.

KW - Account hijacking

KW - Adversarial examples

KW - Evasion attack

KW - trending hashtag

KW - Twitter spam detection

UR - http://www.scopus.com/inward/record.url?scp=85127835147&partnerID=8YFLogxK

U2 - 10.1109/CDMA54072.2022.00011

DO - 10.1109/CDMA54072.2022.00011

M3 - Conference contribution

AN - SCOPUS:85127835147

T3 - Proceedings - 2022 7th International Conference on Data Science and Machine Learning Applications, CDMA 2022

SP - 29

EP - 41

BT - Proceedings - 2022 7th International Conference on Data Science and Machine Learning Applications, CDMA 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th International Conference on Data Science and Machine Learning Applications, CDMA 2022

Y2 - 1 March 2022 through 3 March 2022

ER -