Challenges in Social Network Research. Methods and Applications

Cham : Springer, 2020.

Academic editor: G. Ragozini, M. P. Vitale

We discuss two well-known network measures: the overlap weight of an edge and the clustering coefficient of a node. For both of them it turns out that they are not very useful for data analytic task to identify important elements (nodes or links) of a given network. The reason for this is that they attain their largest values on maximal subgraphs of relatively small size that are more probable to appear in a network than that of larger size. We show how the definitions of these measures can be corrected in such a way that they give the expected results. We illustrate the proposed corrected measures by applying them to the US Airports network using the program Pajek.

Keywords: sociological methods, social network analysis, artificial intelligence, graph theory, data mining and knowledge discovery, Database Management