Quantifying Social And Opportunistic Behavior In Email Networks

Email graphs have been used to illustrate the general properties of social networks of communication and collaboration. However, increasingly, the majority of Internet traffic reflects opportunistic rather than symbiotic social relations. Here we use email data drawn from a large university to construct directed graphs of email exchange that quantify the differences between social and opportunistic behavior, represented by legitimate messages and spam, respectively. We show that while structural characteristics typical of other social networks are shared to a large extent by the legitimate component, they are not characteristic of opportunistic traffic. To complement the graph analysis, which suffers from incomplete knowledge of users external to the domain, we study temporal patterns of communication to show dynamical properties of email traffic. The results indicate that social email traffic has lower entropy (higher structural information) than opportunistic traffic for periods covering both working and non-working hours. We see in general that both social and opportunistic traffics are not random, and that social email shows stronger temporal structure with a high probability for long silences and bursts of a few messages. These findings offer insights into the fundamental differences between social and opportunistic behavior in email networks, and may generalize to the structure of opportunistic social relations in other environments.