Defining and Discovering Communities in Social Networks

Stephen Kelley (), Mark Goldberg, Malik Magdon-Ismail, Konstantin Mertsalov and Al Wallace
Additional contact information
Stephen Kelley: Oak Ridge National Laboratory
Mark Goldberg: Rensselear Polytechnic Institute
Malik Magdon-Ismail: Rensselear Polytechnic Institute
Konstantin Mertsalov: Rensselear Polytechnic Institute
Al Wallace: Rensselear Polytechnic Institute

Chapter Chapter 6 in Handbook of Optimization in Complex Networks, 2012, pp 139-168 from Springer

Abstract: Abstract The categorization of vertices in a network is a common task across a multitude of domains. Specifically, identifying structural divisions into internally well connected sets have been shown to be useful in computer science, social science, and biology. In each of these areas, grouping vertices using structural boundaries helps one to understand the underlying processes of a network. Identifying such groupings is a non-trivial task and has been a subject of intense research in recent years.

Keywords: Community Detection; Normalize Mutual Information; Group Validity; Community Detection Algorithm; Community Detection Method (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (2)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4614-0754-6_6

Ordering information: This item can be ordered from
http://www.springer.com/9781461407546

DOI: 10.1007/978-1-4614-0754-6_6

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().