Modeling the coevolution between citations and coauthorship of scientific papers

2019

Scientometrics

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We provided a game model to simulate the evolution of coauthorship networks, a geometric hypergraph built on a circle. The model expresses kin selection and network reciprocity, two typically cooperative mechanisms, through a cooperation condition called positive benefit-minus-cost. The costs are modelled through space distances. The benefits are modelled through geometric zones that depend on node hyperdegree, which gives an expression of the cumulative advantage on the reputations of authors. Our findings indicate that the model gives a reasonable fitting to empirical coauthorship networks on their degree distribution, node clustering, and so on. It reveals two properties of node attractions, namely node heterogeneity and fading with the growth of hyperdegrees, can deduce the dichotomy of nodes' clustering behavior and assortativity, as well as the trichotomy of degree and hyperdegree distributions: generalized Poisson, power-law and exponential cutoff.

Section: Discussionmentioning

confidence: 99%

A cooperative game model for the multimodality of coauthorship networks

2019

Scientometrics

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“…Does it mean sociable researchers (with many collaborators) will preferentially coauthor with other sociable researchers, and unsociable to unsociable? In a previous study [48], we showed that the proportion of top 5.99% most sociable authors (measured according to degree) having coauthored with another such author is 99.5%. The proportion may even be underestimated, because these authors probably coauthored before 1999 or in other situations.…”

Section: Availability Of Data and Materialsmentioning

confidence: 82%

Feature analysis of multidisciplinary scientific collaboration patterns based on PNAS

et al. 2018

EPJ Data Sci.

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The features of collaboration patterns are often considered to be different from discipline to discipline. Meanwhile, collaborating among disciplines is an obvious feature emerged in modern scientific research, which incubates several interdisciplines. The features of collaborations in and among the disciplines of biological, physical and social sciences are analyzed based on 52,803 papers published in a multidisciplinary journal PNAS during 1999 to 2013. From those data, we found similar transitivity and assortativity of collaboration patterns as well as the identical distribution type of collaborators per author and that of papers per author, namely a mixture of generalized Poisson and power-law distributions. In addition, we found that interdisciplinary research is undertaken by a considerable fraction of authors, not just those with many collaborators or those with many papers. This case study provides a window for understanding aspects of multidisciplinary and interdisciplinary collaboration patterns.

“…3 in Ref. [34]). In fact, signing on a paper of a famous journal will also bring about a huge benefit.…”

Section: Cooperation Cost and Reputation Benefitmentioning

confidence: 91%

“…Coauthorship relationship can be expressed by a hypergraph, where nodes represent authors, and the author group of a paper (called it a "paper team") forms a hyperedge. A number of models have been proposed for generating hypergraphs in specific random ways, and some of them have been used for modelling coauthorship networks [32][33][34]. Meanwhile, there has been an amount of previous work on the structures of specific random hypergraphs, such as clustering, the emergence of a giant component, and so on [35][36][37][38].…”

Section: The Modelmentioning

confidence: 99%

Exploring Cooperative Game Mechanisms of Scientific Coauthorship Networks

2018

Complexity

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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.