Abstract

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.

Notes

Originally published in PLoS ONE 6(12): e28116. 2011. doi:10.1371/journal.pone.0028116

Keywords

dynamical social networks, adaptability

Subject Categories

Social networks, Entropy, Telephone calls, Social interaction

Disciplines

Social Psychology and Interaction

Publisher

Public Library of Science

Publication Date

12-16-2011

Rights Information

© 2011 Zhao et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Rights Holder

Kun Zhao, et al.

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bianconi fig1.tif (438 kB)
Figure 1

bianconi fig2.tif (169 kB)
Figure 2

bianconi fig3.tif (209 kB)
Figure 3

bianconi fig4.tif (79 kB)
Figure 4

bianconi fig5.tif (109 kB)
Figure 5

bianconi fig6.tif (776 kB)
Figure 6

bianconi table1.tif (52 kB)
Table 1

bianconi table2.tif (53 kB)
Table 2

bianconi supp info.pdf (213 kB)
Supporting Information

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