Modelling human communications

This recent paper should be of interest to many at SIS. The authors studied a corpus of text messages (SMS messages) between users to test (and build) models that are useful for characterizing human communications. The authors write:

Our findings reveal that there is a generic Poisson process in individual human behavior which is connected to the power-law-like bursts through the interaction with other individuals, resulting in the interplay between the cut-off time τ0 and the characteristic Poisson interval 1∕β which are generally influenced by the network topology and the processing time tp in various human activities. This picture has significantly changed the current competing views of human activity, either following Poisson or power-law statistics. Our findings open a new perspective in understanding human behavior both at the individual and network level which is of utmost importance in areas as diverse as rumor and disease spreading, resource allocation and emergency response, economics, and recommendation systems, etc. For example, treating the events as independent bursts would allow quantitative analysis of phone line availability and bandwidth allocation in the case of Internet or Web use, which should be significantly different from the assumption of power-law tails which allow very long silent periods.

I wonder how a study like this might apply to more broadly to areas of study within SIS ...