%0 Report
%9 Technical Report
%A Gyongyi, Zoltan
%A Berkhin, Pavel
%A Garcia-Molina, Hector
%A Pedersen, Jan
%D 2005
%F ilprints:697
%I Stanford InfoLab
%K web search; link spam detection
%T Link Spam Detection Based on Mass Estimation
%U http://ilpubs.stanford.edu:8090/697/
%X Link spamming intends to mislead search engines and trigger an artificially high link-based ranking of specific target web pages. This paper introduces the concept of spam mass, a measure of the impact of link spamming on a page's ranking. We discuss how to estimate spam mass and how the estimates can help identifying pages that benefit significantly from link spamming. In our experiments on the host-level Yahoo! web graph we use spam mass estimates to successfully identify tens of thousands of instances of heavy-weight link spamming.