Exploring Cooperative Game Mechanisms of Scientific Coauthorship Networks

Zheng Xie,Jianping Li,Miao Li

doi:10.1155/2018/9173186

Zheng Xie, Jianping Li + Show 1 more

Open Access

https://doi.org/10.1155/2018/9173186

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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, that is, 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, for example, paper team size distribution. The combined effect of modelled costs and reputations reproduces the transitions that emerged in degree distribution, in the correlation between degree and local clustering coefficient, and so on. The model provides an example of how individual strategies induce network complexity, as well as an application of game theory to social affiliation networks.

Highlights

Collaborations between researchers contribute to the breakthrough achievement unattainable by individuals [1, 2] and to the transmission and fusion of knowledge, and they incubate several interdisciplines [3,4,5,6]
The idea has been applied to model coauthorship networks in a geometric way: node influences are modelled by attaching specific geometric zones to nodes [26, 27]
We provide a geometric hypergraph model, where the set of research interests is abstracted as a circle S1, and researchers are expressed as nodes located on the circle (Figure 1)

Summary

Introduction

Collaborations between researchers contribute to the breakthrough achievement unattainable by individuals [1, 2] and to the transmission and fusion of knowledge, and they incubate several interdisciplines [3,4,5,6]. Empirical coauthorship networks have specific common local (degree assortativity, high clustering) and global (fat-tail, small-world) features [12,13,14,15,16,17]. A cooperative game consists of two elements: a set of players and a characteristic function specifying the value (i.e., benefit-minus-cost) created by subsets of players in the game. Modelled cooperative strategies conditioned on positive benefit-minus-cost imitate the spatial reciprocity principle in collaborations [31] and yield high clustering and degree assortativity. The designed form of reputations, together with the strategies, yields the features (hook heads, fat tails [32]) of specific distributions of empirical data, such as degree distribution and the distribution of paper team sizes.

The Model

The Data

Cooperation Cost and Reputation Benefit

Spatial Reciprocity and Network Reputation

Discussions and Conclusions

Conflicts of Interest