Abstract
In this brief review, we discuss some recent findings of human sociality in contemporary techno-social networks of interacting individuals. Here we will focus on a few important observations obtained by analysing mobile communication data of millions of users in a European country participating in billions of calls and text messages over a period of one year. In addition to the description of the basic structure of the network in terms of its topological characteristics like the degree distribution or the clustering coefficient, the demographic information of the users have been utilized to get deeper insight into the various facets of human sociality related to age and gender as reflected in the communication patterns of users. One of the observations suggests that the grandmothering effect is clearly visible in these communication patterns. In addition it is found that the number of friends or connections of a user show a clear decaying trend as a function of the user’s age for both genders. Furthermore, an analysis of the most common location of the users shows the effect of distance on close relationships. As computational analysis and modelling are the two key approaches or tools of modern ‘Social Physics’ we will very briefly discuss the construction of a social network model to get insight into how plausible microscopic social interaction processes translate to meso- and macroscopic socially weighted network structures between individuals.
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Acknowledgements
A.G. and K.K. acknowledge support from project COSDYN, Academy of Finland (Project no. 276439). K.B., D.M. and K.K. acknowledge support from H2020 EU project IBSEN. D.M. acknowledge to CONACYT, Mexico for supporting grant 383907.
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Ghosh, A., Monsivais, D., Bhattacharya, K., Kaski, K. (2017). Social Physics: Understanding Human Sociality in Communication Networks. In: Abergel, F., et al. Econophysics and Sociophysics: Recent Progress and Future Directions. New Economic Windows. Springer, Cham. https://doi.org/10.1007/978-3-319-47705-3_14
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