While Information Communication Technology (ICT) has offered us news ways to communicate and socially interact, it leaves behind digital traces of our individual behavior as records of ever-growing datasets. The study of such data using computational analysis and modeling with Network Theory approach can give us unprecedented insight into human sociality and to the structures and processes of social life and the society. This is well-demonstrated by our analysis of the dataset of mobile phone communication-logs, confirming the Granovetterian picture for the social network structure, i.e. being modular showing communities with strong internal ties and weaker external ties linking them. More recently the same dataset, but with additional data of the gender and age of the service subscribers, has allowed us to look at the nature of social interaction in more detail and from a different Dunbarian egocentric perspective. With this we have got a deeper insight into the gender and age-related social behavior patterns and dynamics of close human relationships.

Talk by Kimmo Kaski.