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Generalizing unweighted network measures to capture the focus in interactions

Authors
  • Abdallah, Sherief1, 2
  • 1 University of Edinburgh, Edinburgh, UK , Edinburgh (United Kingdom)
  • 2 British University in Dubai, Dubai, UAE , Dubai (United Arab Emirates)
Type
Published Article
Journal
Social Network Analysis and Mining
Publisher
Springer Vienna
Publication Date
Feb 18, 2011
Volume
1
Issue
4
Pages
255–269
Identifiers
DOI: 10.1007/s13278-011-0018-8
Source
Springer Nature
Keywords
License
Yellow

Abstract

Unweighted network measures are commonly used to analyze real-world networks due to their simplicity and intuitiveness. This motivated the search for generalizations of unweighted network measures that take weights into account. We propose a new generalization methodology that captures how focused are the interactions over edges. The less focused the interaction (more uniform over edges) the closer is our generalization to the original unweighted measure. None of the previously developed generalizations capture this aspect of weighted networks. We analyze several real-world networks using our generalizations of the degree and the clustering coefficient. The analysis shows that our generalizations reveal interesting observations.

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