The Closeness Centrality Analysis of Fuzzy Social Network Based on Inversely Attenuation Factor
Fuzzy centrality analysis is one of the most important and commonly used tools in fuzzy social network. This is a measurement concept concerning an actor’s central position in the fuzzy social network, and it reflects the different positions and advantage
- PDF / 196,601 Bytes
- 9 Pages / 439.37 x 666.142 pts Page_size
- 29 Downloads / 170 Views
Abstract Fuzzy centrality analysis is one of the most important and commonly used tools in fuzzy social network. This is a measurement concept concerning an actor’s central position in the fuzzy social network, and it reflects the different positions and advantages between social network actors. In this paper we extend the notion of centrality and centralization to the fuzzy framework, propose fuzzy inversely attenuation closeness centrality, and discussed fuzzy group closeness centralization based on inversely attenuation factor in fuzzy social networks. Keywords Fuzzy social network · Attenuation factor · Fuzzy closeness centrality · Fuzzy group closeness centralization
1 Introduction A social network is a set of nodes representing people, groups, organizations, enterprises, etc., that are connected by links showing relations or flows between them. Social network analysis studies the implications of the restrictions of different actors in their communications and then in their opportunities of relation. The fewer constraints an actor faces, the more opportunities he/she will have, and thus he will be in a more favorable position to bargain in exchanges and to intermediate in the bargains of others that need him, increasing his influence. R. Hu · G. Zhang (B) · L. Liao School of Management, Guangdong University of Technology, Guangdong 510520, China e-mail: [email protected] R. Hu e-mail: [email protected] L. Liao e-mail: [email protected]
B.-Y. Cao and H. Nasseri (eds.), Fuzzy Information & Engineering and Operations Research & Management, Advances in Intelligent Systems and Computing 211, DOI: 10.1007/978-3-642-38667-1_46, © Springer-Verlag Berlin Heidelberg 2014
457
458
R. Hu et al.
In social network analysis, the problem of determining the importance of actors in a network has been studied for a long time [1]. It is in this context that the concept of the centrality of a vertex in a network emerged. Social networks analysts consider the closely related concepts of centrality and power as fundamental properties of individuals, that inform us about aspects as who is who in the network, who is a leader, who is an intermediary, who is almost isolated, who is central, who is peripheral. Social networks researchers have developed several centrality measures. Degree, Closeness and Betweenness centralities are without doubt the three most popular ones. Degree centrality focuses on the level of communication activity, identifying the centrality of a node with its degree [2, 3]. Closeness centrality considers the sum of the geodesic distances between a given actor and the remaining as a centrality measure in the sense that the lower this sum is, the greater the centrality [4, 5]. Closeness centrality is, then, a measure of independence in the communications, in the relations or in the bargaining, and thus, it measures the possibility to communicate with many others depending on a minimum number of intermediaries. Betweenness centrality emphasizes the value of the communication control: the possibility t
Data Loading...
