{"title":"Twitter阿拉伯语标签上健康相关活动的实证分析","authors":"Niddal H. Imam, V. Vassilakis, Dimitris Kolovos","doi":"10.1109/CDMA54072.2022.00011","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":313042,"journal":{"name":"2022 7th International Conference on Data Science and Machine Learning Applications (CDMA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Empirical Analysis of Health-Related Campaigns on Twitter Arabic Hashtags\",\"authors\":\"Niddal H. Imam, V. Vassilakis, Dimitris Kolovos\",\"doi\":\"10.1109/CDMA54072.2022.00011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":313042,\"journal\":{\"name\":\"2022 7th International Conference on Data Science and Machine Learning Applications (CDMA)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 7th International Conference on Data Science and Machine Learning Applications (CDMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDMA54072.2022.00011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th International Conference on Data Science and Machine Learning Applications (CDMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDMA54072.2022.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Empirical Analysis of Health-Related Campaigns on Twitter Arabic Hashtags
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.