Identification of Important Actors in Edge-Weight Social Networks
Yiwei Fang, Cui Wentian, Yan Hua-hai
Abstract
Yiwei Fang, Cui Wentian, Yan Hua-hai
Abstract
Identification of important actors is a crucial issue in social network analysis for understanding actor behavior and improving group performance. Many social systems are best described as weighted networks, where nodes represent individual actors and edges represent pairwise relation with varying strength. However, most measures of evaluating actor's importance are limitedly applicable to simple binary social networks, the relation strength being 0 or 1. In this paper we assign weights to social links according to the pairwise relation strength and give a new measure applicable to highlight important actors embedded in an edge-weight network. We also present a simple example and an application in an organization network, both of which prove that in edge-weight social networks our new measure works well in identifying some important actors with which attribute-based centrality measures have difficulties
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Identification of important actors is a crucial issue in social network analysis for understanding actor behavior and improving group performance. Many social systems are best described as weighted networks, where nodes represent individual actors and edges represent pairwise relation with varying strength. However, most measures of evaluating actor's importance are limitedly applicable to simple binary social networks, the relation strength being 0 or 1. In this paper we assign weights to social links according to the pairwise relation strength and give a new measure applicable to highlight important actors embedded in an edge-weight network. We also present a simple example and an application in an organization network, both of which prove that in edge-weight social networks our new measure works well in identifying some important actors with which attribute-based centrality measures have difficulties
Key concepts: Pairwise comparison, Centrality, Relation (database), Identification (biology), Enhanced Data Rates for GSM Evolution, Computer science, Measure (data warehouse), Binary relation