Uncovering fundamentals of social structure across species with generative network modelling

Name of applicant

Josefine Bohr Brask


University of Exeter


DKK 1,720,786



Type of grant

Reintegration Fellowships


Sociality is a fundamental aspect of life on earth, both for humans and many non-human animals. In many species, individuals spend time in close proximity and frequently interact with each other. These patterns of interaction between individuals constitute their social network structure. During the last two decades, such structures have been quantified and scientifically investigated in many species. This project concerns the emergence of social structures. The aim of the project is to gain new fundamental insights into how behaviour on the level of the individual affects social network structure and dynamical processes in the networks, by developing and using a novel modelling framework based on generative network modelling.


Social networks across species show diverse structural patterns. The network structures play an important role for both proximate processes (such as flows of information and disease), and evolutionary processes. This makes them relevant scientific study objects in relation to a range of questions about social evolution, ecology, and complex systems. We now have extensive knowledge about how social networks in different species are structured, and we also have an in-depth understanding of networks as theoretical objects. But to comprehensively understand social systems, we need better insights into the link between individual behaviour and social network structures. An important step towards this is the development of realistic models for the emergence of social network structures.


This project takes an interdisciplinary approach and combines knowledge about social systems across species with theoretical and methodological approaches from the scientific field of networks and complex systems. A key approach in network science is a class of models called generative network models, which are computer algorithms that can generate artificial network structures from defined linking rules. This makes them excellent tools for investigating the link between individual behaviour and social structure. Taking departure in empirical knowledge about social systems across species, I will develop a model based on realistic linking rules and use this to investigate - by computer simulation - how the rules affect network structure and flows in the networks.

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