Abstract
A variety of node-level centrality measures, including purely structural measures (such as degree and closeness centrality) and measures incorporating characteristics of actors (such as the Blau's measure of heterogeneity) have been developed to measure a person's access to resources held by others. Each of these node-level measures can be placed on a continuum depending on whether they focus only on ego's direct contacts (e.g. degree centrality and Blau's measure of heterogeneity), or whether they also incorporate connections to others at longer distances in the network (e.g. closeness centrality or betweenness centrality). In this paper we propose generalized measures, where a tuning parameter δ regulates the relative impact of resources held by more close versus more distant others. We first show how, when a specific δ is chosen degree-centrality and reciprocal closeness centrality are two specific instances of this more general measure. We then demonstrate how a similar approach can be applied to node-level measures that incorporate attributes. When more or less weight is given to other nodes at longer distances with specific characteristics, a generalized measure of resource-richness and a generalized measure for diversity among one's connections can be obtained (following Blau's measure of heterogeneity). Finally, we show how this approach can also be applied to betweenness centrality to focus on more local (ego) betweenness or global (Freeman) betweenness. The importance of the choice of δ is illustrated on some classic network datasets.
Original language | English |
---|---|
Pages (from-to) | 12-26 |
Number of pages | 15 |
Journal | Social Networks |
Volume | 49 |
DOIs | |
State | Published - May 1 2017 |
Bibliographical note
Publisher Copyright:© 2016
Keywords
- Betweenness centrality
- Closeness centrality
- Degree centrality
- Diversity
- Node-level measures
- Resource-richness
ASJC Scopus subject areas
- Anthropology
- Sociology and Political Science
- General Social Sciences
- General Psychology