Social communities detection in Enron corpus using h-Index

Development of modern technologies is expanded with communications possibilities. Electronic systems of communications make possible overcoming of traditional barriers of communication, for example, such as distance. On their basis there are new types of communities which any more have no geographical restrictions. Increasing popularity of electronic communities among which projects LiveJournal, LiveInternet, and also projects popular in Russian-speaking part Internet Mamba, MirTesen, VKontakte, Odnoklassniki, etc., makes as never earlier actual questions on working out of techniques of research of similar social networks. However communications of elements of such communities only on means of electronic communications create difficulties at definition of such communities. There is some question of the specific communities connected with identification and their properties. Nevertheless such communities can be presented graphs, i.e. objects - vertices, and communications channels between them - edges. Thus a number of problems can be solved by means of use of methods from the theory of graphs. In this paper application for such networks of the methods offered for measurement of the importance of scientists work, for the purpose of definition of popularity of objects in community is described and shown. Approach demonstration is made on Enron corpus.