Exploring cooperative game mechanisms of scientific coauthorship networks

TL;DR

This paper introduces a cooperative game model for scientific coauthorship networks that explains their structural features and evolution by modeling collaboration benefits and costs through spatial and reputational factors.

Contribution

It presents a novel cooperative game framework that reproduces key properties of coauthorship networks, linking individual strategies to network complexity.

Findings

Model reproduces high clustering and degree assortativity.

Generates degree distribution transitions and fat tails.

Explains network features through spatial reciprocity and reputation dynamics.

Abstract

Scientific coauthorship, generated by collaborations and competitions among researchers, reflects effective organizations of human resources. Researchers, their expected benefits through collaborations, and their cooperative costs constitute the elements of a game. Hence we propose a cooperative game model to explore the evolution mechanisms of scientific coauthorship networks. The model generates geometric hypergraphs, where the costs are modelled by space distances, and the benefits are expressed by node reputations, i. e. geometric zones that depend on node position in space and time. Modelled cooperative strategies conditioned on positive benefit-minus-cost reflect the spatial reciprocity principle in collaborations, and generate high clustering and degree assortativity, two typical features of coauthorship networks. Modelled reputations generate the generalized Poisson parts and fat tails appeared in specific distributions of empirical data, e. g. paper team size distribution. The combined effect of modelled costs and reputations reproduces the transitions emerged in degree distribution, in the correlation between degree and local clustering coefficient, etc. The model provides an example of how individual strategies induce network complexity, as well as an application of game theory to social affiliation networks.