New computational approaches for understanding the emergence of social network structures

Josefine Bohr Brask says: “Social networks describe the pattern of social connections between individuals in a population. For example, the friendships among children in a school class, the grouping patterns within a dolphin population, and the grooming interactions within a group of chimpanzees, can all be described as a social network, where each node is an individual and the links are their social connections.

Social networks play an important role in the lives of both humans and non-human animals. The structure of the networks affect the spread of disease and information, and the social connectedness of individuals affect their health, well-being and survival. Social networks are therefore of great scientific interest.

A key question about social networks is how the complex structures arise from the behavioural strategies that individuals use to select their social partners. Answering this question is essential for understanding social systems, and for predicting their reaction to future societal and environmental challenges.

In this project, we develop and use new computational methods for the study of networks, within two main methodological regimes: statistical analysis of network data, and simulation of networks via computer algorithms (generative network modelling). Our aim with this is to advance the study of networks and our understanding of the emergence of social network structures.”