Hateful people or hateful bots? Detection and characterization of bots spreading religious hatred in Arabic social media

被引：15
作者：
Albadi N. [1 ,2 ]
Kurdi M. [2 ,3 ]
Mishra S. [2 ]
机构：
[1] Taibah University, Department of Computer Science, Medina
[2] University of Colorado Boulder, Department of Computer Science, 1111 Engineering Dr, Boulder, 80309, CO
[3] Taif University, Department of Computer Science, Taif
来源：
Proceedings of the ACM on Human-Computer Interaction | 2019年 / 3卷 / CSCW期
关键词：
Arabic bots; Arabic NLP; Detection; Hate speech; Machine learning; Twitter;
D O I：
10.1145/3359163
中图分类号：
学科分类号：
摘要：
Arabic Twitter space is crawling with bots that fuel political feuds, spread misinformation, and proliferate sectarian rhetoric. While efforts have long existed to analyze and detect English bots, Arabic bot detection and characterization remains largely understudied. In this work, we contribute new insights into the role of bots in spreading religious hatred on Arabic Twitter and introduce a novel regression model that can accurately identify Arabic language bots. Our assessment shows that existing tools that are highly accurate in detecting English bots don’t perform as well on Arabic bots. We identify the possible reasons for this poor performance, perform a thorough analysis of linguistic, content, behavioral and network features, and report on the most informative features that distinguish Arabic bots from humans as well as the differences between Arabic and English bots. Our results mark an important step toward understanding the behavior of malicious bots on Arabic Twitter and pave the way for a more effective Arabic bot detection tools. © 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.
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