TrollSpot: Detecting misbehavior in commenting platforms

Commenting platforms, such as Disqus, have emerged as a major online communication platform with millions of users and posts. Their popularity has also attracted parasitic and malicious behaviors, such as trolling and spamming. There has been relatively little research on modeling and safeguarding these platforms. As our key contribution, we develop a systematic approach to detect malicious users on commenting platforms. Our work provides two key novelties: (a) we provide a fine-grained classification of malicious behaviors, and (b) we use a comprehensive set of 73 features that span four dimensions of information. We use 7 million comments during a 9 month period, and we show that our classification methods can distinguish between benign, and malicious roles (spammers, trollers, and fanatics) with a 0.904 AUC. Our work is a solid step towards ensuring that commenting platforms are a safe and pleasant medium for the exchange of ideas.