  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.
