Using PageRank to Characterize Web Structure

Gopal Pandurangan, Prabhakar Raghavan, Eli Upfal
2006 Internet Mathematics  
Recent work on modeling the Web graph has dwelt on capturing the degree distributions observed on the Web. Pointing out that this represents a heavy reliance on "local" properties of the Web graph, we study the distribution of PageRank values (used in the Google search engine) on the Web. This distribution is of independent interest in optimizing search indices and storage. We show that PageRank values on the Web follow a power law. We then develop detailed models for the Web graph that explain
more » ... graph that explain this observation, and moreover remain faithful to previously studied degree distributions. We analyze these models, and compare the analyses to both snapshots from the Web and to graphs generated by simulations on the new models. To our knowledge this represents the first modeling of the Web that goes beyond fitting degree distributions on the Web.
doi:10.1080/15427951.2006.10129114 fatcat:hpv22nsodzdfnfgzgxczwmjeqe