Journal article

Matching–centrality decomposition and the forecasting of new links in networks

  • Rohr, Rudolf P. Department of Biology–Ecology and Evolution, University of Fribourg, Switzerland - Integrative Ecology Group, Estación Biológica de Doñana, EBD-CSIC, Sevilla, Spain
  • Naisbit, Russell E. Department of Biology–Ecology and Evolution, University of Fribourg, Switzerland
  • Mazza, Christian Department of Mathematics, University of Fribourg, Switzerland
  • Bersier, Louis-Félix Department of Biology–Ecology and Evolution, University of Fribourg, Switzerland
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    10.02.2016
Published in:
  • Proc. R. Soc. B. - 2016, vol. 283, no. 1824, p. 20152702
English Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching–centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network.
Faculty
Faculté des sciences et de médecine
Department
Département de Biologie, Département de Mathématiques
Language
  • English
Classification
Ecology
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/304739
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