Natural Language Processing Lab National Taiwan University The splog Detection Task and A Solution...

Natural Language Processing LabNational Taiwan University

The splog Detection Task and A Solution Based on Temporal and Link PropertiesYu-Ru Lin et al.

NEC AmericaTREC 2006 (Blog session)

Presentor: Chun-Yuan Teng


Splog characteristics• Machine-generated content• No Value-addition

– No unique information to their readers• Hidden agenda, usually an economic

goal– Commercial intention


Uniqueness of splogs• Dynamic content

– Unlike web spam, a splog generates fresh content to drive traffic

• Non-endorsement link– Hyperlink is an endorsement of other pages– Spammers can create hyperlinks in normal bl

ogs, links in blogs is not endorsement


Features to detect splog• Traditional features

– Tokenized URL, blog and post titles, homepage content, and post content

• Temporal regularity– Temporal content regularity/Temporal

structural regularity• Link regularity

– Consistency in target website


Temporal Content Regularity


Temporal Structural Regularity


Link Regularity estimation


Two kinds of spam detection

• Offline detection– Traditional measurement

• Online detection– Detect spam online


Experimental Result (Offline)


Experimental results (Offline)


Online indexing in blog search engine


Online test


Online test in this paper


Experimental results


Conclusion and contributions

• Modeling the splog problem– The uniqueness of splog

• Regularity based detection– Content and post time

• Evaluation– Online evaluation

Natural Language Processing Lab National Taiwan University The splog Detection Task and A Solution...

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