Analyzing community structure in networks

Hongyuan Zhan, Kamesh Madduri

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

1 Scopus citations

Abstract

Real-world networks exhibit significant community structure. Communities are sometimes explicitly known or defined (e.g., virtual groups that one joins in an online social network, departments in an organization), but are often determined using a community detection or a clustering algorithm. Given a weighted network, with edge weights denoting interaction strengths between vertices, and a community membership matrix mapping vertices to overlapping or non-overlapping communities, we present a new unsupervised method for analyzing and ranking these communities, such that the computed nonnegative community weights seek to explain the edge weights. Our method is based on a new factorization of the weighted adjacency matrix. The weighted matrix decomposition we obtain has a simple combinatorial interpretation. We show that the proposed optimization problem reduces to a Nonnegative Least Squares problem, and design a fast algorithm for computing the community weights. We assess this problem formulation on a variety of synthetic and real-world networks, in order to gain insight into its advantages and limitations.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1540-1547
Number of pages8
ISBN (Electronic)9781538634080
DOIs
StatePublished - Jun 30 2017
Event31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017 - Orlando, United States
Duration: May 29 2017Jun 2 2017

Other

Other31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017
CountryUnited States
CityOrlando
Period5/29/176/2/17

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Networks and Communications
  • Information Systems

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