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Reseach Article

Structural Pattern Analysis in Telecom Social Networks

by Pushpa Ravikumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 113 - Number 6
Year of Publication: 2015
Authors: Pushpa Ravikumar
10.5120/19830-1681

Pushpa Ravikumar . Structural Pattern Analysis in Telecom Social Networks. International Journal of Computer Applications. 113, 6 ( March 2015), 21-26. DOI=10.5120/19830-1681

@article{ 10.5120/19830-1681,
author = { Pushpa Ravikumar },
title = { Structural Pattern Analysis in Telecom Social Networks },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 113 },
number = { 6 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 21-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume113/number6/19830-1681/ },
doi = { 10.5120/19830-1681 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:50:15.279637+05:30
%A Pushpa Ravikumar
%T Structural Pattern Analysis in Telecom Social Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 113
%N 6
%P 21-26
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The social network perspective emphasizes multiple levels of analysis. Differences among Customers are traced to the constraints and opportunities that arise from how they are embedded in networks, the structure and behavior of networks grounded in, and enacted by local interactions among customers. This paper addresses the local connections of customers in which it deals with social behavior of the whole population, as well as for understanding each individual. However this paper explains the structural patterns of Telecom social network in the form of network connection analysis and network distance analysis. A social network connection involves Demographics, density, reachability and connectivity of customers who are embedded in the network. Network distance analysis describes the walks, geodesic distance and flow between the customers. Populations with high density respond differently to challenges from the environment than those with low density, populations with greater diversity in individual densities may be more likely to develop stable social differentiation and stratification.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Reachability Demography Connectivity Geodesic Density Walks Reachability