Social Network Analysis Project: Telecom Data Analysis and Planning

This project focuses on Social Network Analysis (SNA) applied to telecommunication networks, leveraging graph theory to analyze social communication. The project utilizes telecom data, including customer data and Call Detail Records (CDR), to model relationships and identify customer groups with similar properties. The project outlines objectives such as gathering information about relationships, defining target groups, and data collection methods. A project schedule spanning 80 days from December 2018 to March 2019 is presented, along with a Gantt chart illustrating the timeline. The developmental methodology is based on graph theory and network analysis. Key success factors include effective connectivity and real-time monitoring, while assumptions, constraints, and risks related to security and costs are also addressed. References to relevant research papers are provided to support the project's theoretical basis and practical application.

0
Project Plan: Social Network Analysis
Student Name:
Student Id:
Tutor’s Name:
Word Count:

1
Executive Summary
This project focusses on the social network analysis or SNA which is considered the analysis
for social communication as per the network as per the graph theory. The application of SNA
has been found exploring the telecommunication domain. Therefore, the telecom data
consists the customer data along with the Call Detail Data or CDR (Kim & Hastak, 2018). It
is referred to the proposed work as it is considered as the attributes for call detail data as well
as customer data. It has the main criteria for relationship types for the model with Multi-
relational Telecommunication for the social network. Therefore, the social network analysis
is considered as it includes the discovery of a group on the basis of customers as it shares a
similar type of properties. In this project, the social structure for the organization will be
described through groupings.

2
Table of Contents
Executive Summary...................................................................................................................1
Introduction................................................................................................................................3
Project Background....................................................................................................................3
Project Objectives......................................................................................................................3
Project schedule.........................................................................................................................4
Gantt chart..............................................................................................................................4
Developmental Methodology.....................................................................................................5
Key Success Factors...................................................................................................................6
Assumptions, Constraints and Risks..........................................................................................6
References..................................................................................................................................7

3
Introduction
This project focusses on the social network analysis or SNA in the telecommunication
networks. It is also found that the social network analysis process where it is needed to detect
the innovation processes in this communication field (Bilecen, Gamper, & Lubbers, 2018).
The network structure is found to characterize in terms of the actors, people as well as the
things as it is found to associate with the ties or the links. In this scenario, the network is
found to establish with the person, groups along with the organizations.
Project Background
The knowledge acquisition for telecom customers has been consumed the behaviour as it is
depending on the data mining concepts as it is described through Chungfang Zhao. It is the
customer analysis model which is needed to take a method for data mining as it includes the
customer segmentation analysis. There is the customer churn analysis as it is depending on
the client information data, billing data as well as the customer care data.
As per Hong Feng Lai, it has been proposed that the framework is needed to extract the
implicit social network in order to interpret various other features for social networks. In case
to express the implicit social network it has been proposed that there is the set as well as the
frame logic which represents the implicit relationship within the framework.
Project Objectives
The objective of Social Network Analysis involves as follows:
1. It is needed to gather the information as the relationships with the specified group or the
network for the people.

4
2. It is needed to define the target group for the network.
3. Thereby, the data collection with the specific needs as well as the problems will be
performed by taking interview of the managers.
4. It is needed to detect as well as explain the scope as well as the aim of analysis.
5. It is needed to identify the required level in case of reporting.
6. It is needed to form the questions as well as the solution.
7. It is needed to develop the questionnaire along with the survey method (Tulin, Pollet, &
Lehmann-Willenbrock, 2018).
8. It is needed to detect the network by interviewing the personnel.
9. It is needed to create the base for the analysis of data with the survey resources.
10. It is needed to change the actions which can be designed as well as implemented.
Project schedule
This schedule of the project is on 80 days from 3rd December 2018 to 22nd March 2019.
Gantt chart
The Gantt chart is as follows:

5
Developmental Methodology
The whole project of the network analysis in telecommunication is based on the graph theory
and network analysis. As per the network analysis concerned, there is the formulation as well
as the solution for the problems which has the network structures and it is usually captured
through the graph.
This graph theory is found to provide the set of abstract concepts as well as methods on
behalf of the analysis of graphs. There are the combinations for analytical tools where the

6
methods are developed in specifically for the visualization as well as analysis of the social
networks on the basis which is needed to call the SNA methods.
Also, the SNA is not just a methodology, but it indicates a unique perspective for which there
would be a society functions. Also, it is focussing on the individuals along with the attributes
for macroscopic social structure which centres the relations within the individuals, group as
well as social institutions.
Key Success Factors
1. Most effective and should have maximum connectivity.
2. Useful at any time and uses as the real-time monitoring for the social web
Assumptions, Constraints and Risks
1. The security system should be strong enough so that any unauthorised person cannot enter
through administer or the employees’ login credentials in the network zone.
2. Hidden links should not be detected as per the data or connect the individual by utilising
multiple identities.
3. The network system should be performed by utilising very low cost as compared with the
available SNA market products (Kim & Hastak, 2018).

7
References
Bilecen, B., Gamper, M., & Lubbers, M. J. (2018). The missing link: Social network analysis
in migration and transnationalism. Social Networks, 1-3.
Huitsing, G., & Monks, C. P. (2018). Who victimizes whom and who defends whom? A
multivariate social network analysis of victimization, aggression, and defending in
early childhood. Aggressive behaviour, 10-16.
Kim, J., & Hastak, M. (2018). Social network analysis: Characteristics of online social
networks after a disaster. International Journal of Information Management, 86-97.
Oldenburg, B., Van Duijn, M., & Veenstra, R. (2018). Defending one's friends, not one's
enemies: A social network analysis of children's defending, friendship, and dislike
relationships using XPNet. PloS one, e0194323.
Tulin, M., Pollet, T. V., & Lehmann-Willenbrock, N. (2018). Perceived group cohesion
versus actual social structure: A study using social network analysis of egocentric
Facebook networks. Social Science Research, 1-8.