Using spam farm to boost PageRank
Ye Du, Yaoyun Shi, Xin Zhao · 2007
Nowadays web spamming has emerged to take the economic advantage of high search rankings and threatened the accuracy and fairness of those rankings. Understanding spamming techniques is essential for evaluating the strength and weakness of a ranking algorithm, and for fighting against web spamming. In this paper, we identify the optimal spam farm structure under some realistic assumptions in the single target spam farm model. Our result extends the optimal spam farm claimed by Gyöngyi and Garcia-Molina through dropping the assumption that leakage is constant. We also characterize the optimal spam farms under additional constraints, which the spammer may deploy to disguise the spam farm by deviating from the unconstrained optimal structure.