1. Detecting Web Spam with CombinedRank Abhita Chugh Ravi Tiruvury

2. 0.05 0.13 0.05 0.12 0.15 0 0.18 Motivation  TrustRank Starts with a seed set of good pages Propagates trust to each page reachable by the trusted seed set. Drawback: Can assign a high “Trust” score to a spam page! 1 4 2 5 3 6 good bad x.yz TrustRank score 7  Anti-Trust Rank Starts with a seed set of spam pages Propagates distrust to each page reachable by the spam seed set in the inverse webgraph. Benefit: Assigns high “Anti-Trust” scores to spam pages

3. CombinedRank  Combines TrustRank and Anti-Trust Rank  Each node in the webgraph has a Trust score and an Anti- Trust score  High Trust Score & High Anti-Trust Score => Potentially Spam!  Best results with α = 1.0 and β = 0.8 CombinedRank = α * (TrustRank) – β * (Anti-Trust Rank)

4. Results