A new closeness metric for social networks based on the k shortest paths

  • Authors:
  • Chun Shang;Yuexian Hou;Shuo Zhang;Zhaopeng Meng

  • Affiliations:
  • Department of Computer Science and Technology, Tianjin University, Tianjin, China;Department of Computer Science and Technology, Tianjin University, Tianjin, China;Department of Computer Science and Technology, Tianjin University, Tianjin, China;Department of Computer Science and Technology, Tianjin University, Tianjin, China

  • Venue:
  • ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
  • Year:
  • 2010

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Abstract

We axiomatically develop a metric of personal connection between individuals in social networks, and construct an optimal model to find the best weight of the metric Our metric optimizes, in some strict-established sense, weighted average of the k shortest paths so that it is able to distinguish the closeness between nodes more relevantly than traditional metrics The algorithms are implemented and evaluated on random networks and real social networks data The results demonstrate relevance and correctness of our formalization.