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Science
Vol. 328 no. 5980 pp. 876-878
DOI: 10.1126/science.1184819
  • Report

Community Structure in Time-Dependent, Multiscale, and Multiplex Networks

  1. Jukka-Pekka Onnela6,7

+ Author Affiliations

  1. 1Carolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina, Chapel Hill, NC 27599, USA.
  2. 2Institute for Advanced Materials, Nanoscience and Technology, University of North Carolina, Chapel Hill, NC 27599, USA.
  3. 3Operations Research, North Carolina State University, Raleigh, NC 27695, USA.
  4. 4Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, Oxford OX1 3LB, UK.
  5. 5CABDyN Complexity Centre, University of Oxford, Oxford OX1 1HP, UK.
  6. 6Department of Health Care Policy, Harvard Medical School, Boston, MA 02115, USA.
  7. 7Harvard Kennedy School, Harvard University, Cambridge, MA 02138, USA.
  1. *To whom correspondence should be addressed. E-mail: mucha@unc.edu

Network science is an interdisciplinary endeavor, with methods and applications drawn from across the natural, social, and information sciences. A prominent problem in network science is the algorithmic detection of tightly connected groups of nodes known as communities. We developed a generalized framework of network quality functions that allowed us to study the community structure of arbitrary multislice networks, which are combinations of individual networks coupled through links that connect each node in one network slice to itself in other slices. This framework allows studies of community structure in a general setting encompassing networks that evolve over time, have multiple types of links (multiplexity), and have multiple scales.

  • Received for publication 17 November 2009.
  • Accepted for publication 22 March 2010.

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