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Novel Edge and Density Metrics for Link Cohesion

  • Cetin Savkli
  • Catherine Schwartz
  • Amanda GalanteEmail author
  • Jonathan Cohen
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 881)

Abstract

We present a new metric of link cohesion for measuring the strength of edges in complex, highly connected graphs. Link cohesion accounts for local small hop connections and associated node degrees and can be used to support edge scoring and graph simplification. We also present a novel graph density measure to estimate the average cohesion across nodes. Link cohesion and the density measure are employed to demonstrate community detection through graph sparsification by maximizing graph density. Link cohesion is also shown to be loosely correlated with edge betweenness centrality.

Keywords

Link cohesion Graph sparsification Graph density Centrality Community detection 

Notes

Acknowledgments

This work was supported by internal research and development funding provided by Johns Hopkins University Applied Physics Laboratory. Algorithms were implemented with SOCRATES [23] and visualized with an internal tool, Pointillist.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Cetin Savkli
    • 1
  • Catherine Schwartz
    • 1
  • Amanda Galante
    • 1
    Email author
  • Jonathan Cohen
    • 1
  1. 1.Johns Hopkins University Applied Physics LaboratoryLaurelUSA

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