Weighted node degree centrality for hypergraphs

Komal Kapoor, Dhruv Sharma, Jaideep Srivastava

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Many real-world social interactions involve multiple people, for e.g., authors collaborating on a paper, email exchanges made in a company and task-oriented teams in workforce. Simple graph representation of these activities destroys the group structure present in them. Hypergraphs have recently emerged as a better tool for modeling group interactions. However, methods in social hypernetwork analysis haven't kept pace. In this work, we extend the concept of node degree centrality to hypergraphs. We validate our proposed measures using alternate measures of influence available to us using two datasets namely, the DBLP dataset of scientific collaborations and the group network in a popular Chinese multi-player online game called CR3. We discuss several schemes for assigning weights to hyperedges and compare them empirically. Finally, we define separate weak and strong tie node degree centralities which improves performance of our models. Weak tie degree centrality is found to be a better predictor of influence in hypergraphs than strong tie degree centrality.

Original languageEnglish
Title of host publicationProceedings of the 2013 IEEE 2nd International Network Science Workshop, NSW 2013
Pages152-155
Number of pages4
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 IEEE 2nd International Network Science Workshop, NSW 2013 - West Point, NY
Duration: 29 Apr 20131 May 2013

Other

Other2013 IEEE 2nd International Network Science Workshop, NSW 2013
CityWest Point, NY
Period29/4/131/5/13

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Keywords

  • centrality
  • degree
  • Hypergraph

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Kapoor, K., Sharma, D., & Srivastava, J. (2013). Weighted node degree centrality for hypergraphs. In Proceedings of the 2013 IEEE 2nd International Network Science Workshop, NSW 2013 (pp. 152-155). [6609212] https://doi.org/10.1109/NSW.2013.6609212

Weighted node degree centrality for hypergraphs. / Kapoor, Komal; Sharma, Dhruv; Srivastava, Jaideep.

Proceedings of the 2013 IEEE 2nd International Network Science Workshop, NSW 2013. 2013. p. 152-155 6609212.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kapoor, K, Sharma, D & Srivastava, J 2013, Weighted node degree centrality for hypergraphs. in Proceedings of the 2013 IEEE 2nd International Network Science Workshop, NSW 2013., 6609212, pp. 152-155, 2013 IEEE 2nd International Network Science Workshop, NSW 2013, West Point, NY, 29/4/13. https://doi.org/10.1109/NSW.2013.6609212
Kapoor K, Sharma D, Srivastava J. Weighted node degree centrality for hypergraphs. In Proceedings of the 2013 IEEE 2nd International Network Science Workshop, NSW 2013. 2013. p. 152-155. 6609212 https://doi.org/10.1109/NSW.2013.6609212
Kapoor, Komal ; Sharma, Dhruv ; Srivastava, Jaideep. / Weighted node degree centrality for hypergraphs. Proceedings of the 2013 IEEE 2nd International Network Science Workshop, NSW 2013. 2013. pp. 152-155
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