Over the last seven decades, graph theory has played an increasingly important role in social network analysis; social networks can be modeled using graphs and the properties of the networks as well as the actors within them can be studied and explored using graph theoretic means. One particular application of graph theory in social network analysis is that of identifying the most ‘important’ or ‘central’ actor or actors in a social network. As importance can be interpreted

in different ways, various motivations lead to different measures of centrality and many of the terms used to measure centrality reflect their sociological origins [7, 16]. In 1979, Freeman [8] identified degree centrality, closeness centrality, and betweenness centrality as both relatively simple and widely applicable measures of centrality. However, when it comes to distance-based measures, eccentricity is arguably a much simpler notion than closeness [20]. The eccentricity eG(v) of a node v in a connected network G is the maximum distance 1 (in the network) between v and u, over all nodes u of G. Figure 1 shows a simple network with the eccentricity of each node. For a disconnected network, all nodes are defined to have infinite eccentricity

see https://hal.archives-ouvertes.fr/hal-01385481/document

(Title of the paper: Eccentricity of Networks with Structural Constraints )

Dear Naji,

Thank you so much.

Analysis of financial networks to assess financial stability is an important task to the central bank of a country. Here it is useful. So much bibliography is on the Internet.

Dvs Sastry ,

Thanks my dear.

Analysis of financial networks to assess financial stability is an important task to the central bank of a country. Here it is useful. So much bibliography is on the Internet.

Dear Nabaa Hasoon كلية التربية للبنات ,

Thanks for your reply.

Great Naji