A Network Formation Model for Collaboration Networks

  • Ankur SharmaEmail author
  • S. Durga BhavaniEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11319)


In social networks, a network grows by following certain rules and patterns, e.g. a collaboration network in which authors come together and publish an article. These authors might have collaborated previously, or they may collaborate in the future with other authors. That is how a collaboration network grows. Collaboration networks are represented as graphs where nodes denote authors and edges between nodes indicate a collaboration between the corresponding authors. There are very few network formation models specific to collaboration networks in the literature. In this work, a novel network formation model that can imitate the growth of a collaboration network is proposed. The main idea is based on the arrival distribution of the numbers of authors collaborating for the papers. We find that Exponential distribution matches best for this process simulation. We have used DBLP dataset to analyze and find the patterns in the network. We show that the network generated by the proposed model is closer to the original network than that of Shi et al. The model has to be further refined in order to improve the results for average clustering coefficient and density of the network.


Network formation model Social networks Collaboration network DBLP 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Computer and Information SciencesUniversity of HyderabadHyderabadIndia

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