Mining User Comment Activity for Detecting Forum Spammers in YouTube
Ashish Sureka

TL;DR
This paper introduces a method to automatically detect YouTube comment spammers by analyzing user activity patterns, such as comment timing and repetition, demonstrating effectiveness through empirical analysis.
Contribution
It presents a novel approach to spam detection in YouTube comments by mining user activity logs and identifying spam behavior patterns.
Findings
Effective detection of comment spammers demonstrated
Patterns like comment timing and repetition are indicative of spam
Empirical results validate the proposed method
Abstract
Research shows that comment spamming (comments which are unsolicited, unrelated, abusive, hateful, commercial advertisements etc) in online discussion forums has become a common phenomenon in Web 2.0 applications and there is a strong need to counter or combat comment spamming. We present a method to automatically detect comment spammer in YouTube (largest and a popular video sharing website) forums. The proposed technique is based on mining comment activity log of a user and extracting patterns (such as time interval between subsequent comments, presence of exactly same comment across multiple unrelated videos) indicating spam behavior. We perform empirical analysis on data crawled from YouTube and demonstrate that the proposed method is effective for the task of comment spammer detection.
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Taxonomy
TopicsSpam and Phishing Detection · Sentiment Analysis and Opinion Mining · Network Security and Intrusion Detection
