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.

This paper proposes a novel method for identifying the largest and most sophisticated spam farms, by turning the spammers’ ingenuity against themselves. Our focus is on spamming attempts that target PageRank. We introduce the
concept of spam mass, a measure of how much PageRank a
page accumulates through being linked to by spam pages.
The target pages of spam farms, whose PageRank is boosted...