Temporal networks are networks where each link can appear at a given time and can disappear later on.
Social contacts including face-to face interactions, and mobile phone communication are a beautiful examples of temporal networks where the link has a non-uniform duration.
I have investigated several models of temporal networks for describing face-to face interactions and mobile phone communication comparing the models to real datasets.
- Face-to-face interactions are characterized by a bursty behavior. Therefore the distribution of the duration of the interactions follows a power-law. This phenomenon can be captured by a reinforcement dynamics according to which the longer an interaction last, the less probable it is that it ends.
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The duration of phone calls, instead, does not follows a power-law distribution but a Weibull distribution. This distribution can always be explained by a reinforcement rule but the functional form that implements this rule differs with respect to the case of face-to-face interactions.
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The compairison of the distribution of duration of face-to-face interactions and mobile phone calls has allowed us to conclude that the bursty human behavior is able to significantly adapt to the technology. In particular the two different means of communication carry different level of information and predicatbility as captured by the entropy of dynamical temporal networks.