Internet user behavior: compared study of the access traces and application to the discovery of communities

With an ever-increasing emphasis on human activity (idea exchange, shopping, gaming, etc.) being mediated through the data network, the understanding of Internet users' behavior has become a rising challenge. Research dealing with the analysis and modeling of Internet user behavior can be roughly split in to two main approaches. The first is based on sociocognitive observation of users' practices in a standardized context. The second approach focuses on the analysis of productions and the traces of users' activity. This paper relates to the latter approach and presents a comparative analysis of Internet navigation traces (URLs versus keywords) to characterize individual or group-of-users' behavior when accessing the Web. The proposed models are based on the study of accesses redundancy seen as global static parameters and from the angle of time evolution. We also study the use of these models, in particular, to categorize a population of users in communities of interests. This study enables us to draw some conclusions on the compared performances of the two kinds of trace exploitation, as raw information, as well as the self-similar properties of the models.