NDLI: Social communities detection in Enron corpus using h-Index

Content Provider	IEEE Xplore Digital Library
Author	Timofieiev, A. Snasel, V. Dvorsky, J.
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci., VSB-Tech. Univ. of Ostrava, Ostrava (Timofieiev, A.; Snasel, V.; Dvorsky, J.)
Abstract	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.
Starting Page	507
Ending Page	512
File Size	695017
Page Count	6
File Format	PDF
ISBN	9781424426232
DOI	10.1109/ICADIWT.2008.4664401
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-04
Publisher Place	Czech Republic
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article

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