CFP last date
20 May 2024
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
  1. Shaun Doyle, "Social network analysis in the Telco sector Marketing applications", Journal of Database Marketing & Customer Strategy Management (2008) 15, pp130-134. doi: 10. 1057/dbm. 2008. 8
  2. Chung fang Zhao, Yingliang Wu, HaijunGao "Study on Knowledge Acquisition of the Telecom Customer' Consuming Behavior Based on Data Mining", 2008 IEEE.
  3. Hong Feng Lai, "Identify implicit social network by RST/FL framework", 2009, Advances in Social Network Analysis and Mining (IEEE Computer Society), pp. 362- 363, DOI 10. 1109/ASONAM. 2009. 62.
  4. Parthan Kasarapu M. Saravanan Prasad Garigipati, "Exploring Social Patterns in Mobile Data", Second International Conference on Advances in Databases, Knowledge, and Data Applications, 2010, pp. 62-68.
  5. Aarthi. S&Bharanidharan. SSaravanan. M&Anand. V," Predicting Customer Demographics in A Mobile Social Networks" , 2011 International Conference on Advances in Social Networks Analysis and Mining (IEEE), pp553-554.
  6. Victor Ströele, Geraldo Zimbrão, Jano M. Souza," Evaluating Knowledge Flow in Multi relational Scientific Social Networks ", Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design, 2011 (IEEE), pp516-523.
  7. Hially Rodrigues de S´a and Ricardo B. C. Prudˆencio, "Supervised Link Prediction in Weighted Networks", Proceedings of International Joint Conference on Neural Networks, San Jose, California, USA, July 31 August 5, 2011,pp 2281-2288.
  8. Namhyoung Kim ,"A New Ensemble Model for Efficient Churn Prediction in Mobile Telecommunication", in 45th Hawaii International Conference on System Science (HICSS), Date of Conference: 4-7 Jan. South Korea 2012,pp 1023 – 1029.
Index Terms

Computer Science
Information Sciences

Keywords

Reachability Demography Connectivity Geodesic Density Walks Reachability