From Trolling to Cyberbullying: Using Machine Learning and Network Analysis to Study Anti-Social Behavior on Social Media

被引:0
|
作者
Gruzd, Anatoliy [1 ]
Mai, Philip [1 ]
Soares, Felipe Bonow [2 ]
机构
[1] Toronto Metropolitan Univ, Social Media Lab, Toronto, ON, Canada
[2] Univ Arts London, London Coll Commun, London, England
关键词
anti-social; online discourse; toxicity analysis; social network analysis; trolling; cyberbullying; computational social science;
D O I
10.1145/3603163.3610531
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The rise of social media and other web and mobile applications has transformed how people interact, but it has also created new challenges, such as anti-social behavior like trolling, cyberbullying, and hate speech. This behavior can have severe negative consequences for individuals and communities. This tutorial is intended for researchers and practitioners interested in computational social science and provides an overview of how to use machine learning and social network analysis techniques to detect and examine anti-social behavior in online discourse.
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