Agents, bookmarks and clicks: a topical model of web navigation
Mark Meiss, Bruno Gonçalves, José J. Ramasco, Alessandro Flammini · 2010
Analysis of aggregate and individual Web traffic has shown that PageRank is a poor model of how people navigate the Web. Us-ing the empirical traffic patterns generated by a thousand users, we characterize several properties of Web traffic that cannot be repro-duced by Markovian models. We examine both aggregate statistics capturing collective behavior, such as page and link traffic, and in-dividual statistics, such as entropy and session size. No model cur-rently explains all of these empirical observations simultaneously. We show that all of these traffic patterns can be explained by an agent-based model that takes into account several realistic browsing behaviors. First, agents maintain individual lists of bookmarks (a non-Markovian memory mechanism) that are used as teleportation targets. Second, agents can retreat along visited links, a branch-ing mechanism that also allows us to reproduce behaviors such as