An Algorithm to Condense Social Networks and Identify Brokers

Luis Cavique, Nuno Miguel Cavalheiro Marques, Jorge M. A. Santos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


In social network analysis the identification of communities and the discovery of brokers is a very important issue. Community detection typically uses partition techniques. In this work the information extracted from social networking goes beyond cohesive groups, enabling the discovery of brokers that interact between communities. The partition is found using a set covering formulation, which allows the identification of actors that link two or more dense groups. Our algorithm returns the needed information to create a good visualization of large networks, using a condensed graph with the identification of the brokers.
Original languageEnglish
Title of host publicationAdvances in Artificial Intelligence - IBERAMIA 2014
Subtitle of host publication14th Ibero-American Conference on AI, Santiago de Chile, Chile, November 24-27, 2014, Proceedings
EditorsAna L.C. Bazzan, Karim Pichara
Place of PublicationCham
PublisherSpringer International Publishing
ISBN (Electronic)978-3-319-12027-0
ISBN (Print)978-3-319-12026-3
Publication statusPublished - 2014
Event14th Ibero-American Conference on Artificial Intelligence (IBERAMIA 2014) - Santiago de Chile, Chile
Duration: 24 Nov 201427 Nov 2014
Conference number: 14th

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
ISSN (Print)0302-9743


Conference14th Ibero-American Conference on Artificial Intelligence (IBERAMIA 2014)
Abbreviated titleIBERAMIA 2014
CitySantiago de Chile


  • Brokerage
  • Condensed network
  • Data mining
  • Graph mining
  • Social networks


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