2 research outputs found
Entropy of dynamical social networks
Human dynamical social networks encode information and are highly adaptive.
To characterize the information encoded in the fast dynamics of social
interactions, here we introduce the entropy of dynamical social networks. By
analysing a large dataset of phone-call interactions we show evidence that the
dynamical social network has an entropy that depends on the time of the day in
a typical week-day. Moreover we show evidence for adaptability of human social
behavior showing data on duration of phone-call interactions that significantly
deviates from the statistics of duration of face-to-face interactions. This
adaptability of behavior corresponds to a different information content of the
dynamics of social human interactions. We quantify this information by the use
of the entropy of dynamical networks on realistic models of social
interactions