In this paper, a new statistical user model for the Internet access is presented. Real traces of Internet traffic in a heterogeneous campus network are analysed. We find three clearly different styles of individual user's behaviour, study their common features and group particular users behaving alike in three clusters. This allows us to build a probabilistic mixture model that implements the expected global behaviour for the different types of users. The implications of this emergent phenomenology are discussed in the field of multi-agent complex systems.