Mining User Comment Activity for Detecting Forum Spammers in YouTube

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.