Ties often have a strength naturally associated with them that differentiate them from each other. Tie strength has been operationalized as weights. A few network measures have been proposed for weighted networks, including three common measures of node centrality: degree, closeness, and betweenness. However, these generalizations have solely focused on tie weights, and not on the number of ties, which was the central component of the original measures. This paper proposes generalizations that combine both these aspects. We illustrate the benefits of this approach by applying one of them to Freeman's EIES dataset. © 2010 Elsevier B.V.

Node centrality in weighted networks: Generalizing degree and shortest paths / Opsahl, T.; Agneessens, F.; Skvoretz, J.. - In: SOCIAL NETWORKS. - ISSN 0378-8733. - 32:3(2010), pp. 245-251. [10.1016/j.socnet.2010.03.006]

Node centrality in weighted networks: Generalizing degree and shortest paths

Agneessens F.;
2010-01-01

Abstract

Ties often have a strength naturally associated with them that differentiate them from each other. Tie strength has been operationalized as weights. A few network measures have been proposed for weighted networks, including three common measures of node centrality: degree, closeness, and betweenness. However, these generalizations have solely focused on tie weights, and not on the number of ties, which was the central component of the original measures. This paper proposes generalizations that combine both these aspects. We illustrate the benefits of this approach by applying one of them to Freeman's EIES dataset. © 2010 Elsevier B.V.
2010
3
Opsahl, T.; Agneessens, F.; Skvoretz, J.
Node centrality in weighted networks: Generalizing degree and shortest paths / Opsahl, T.; Agneessens, F.; Skvoretz, J.. - In: SOCIAL NETWORKS. - ISSN 0378-8733. - 32:3(2010), pp. 245-251. [10.1016/j.socnet.2010.03.006]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/247393
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