Analysis of social network for telecommunication companies

Social Network Analysis (SNA) is defined as the science of grouping members and finding influencers member inside each group by utilizing advanced set of algorithms. Most specialized data mining software firms, such as IBM, SAS, python and R, create their own predefined algorithms for generating the SNA groups, but none of them is dedicated for the telecom industry. The aim of this paper is to develop a customized SNA algorithm for the telecom industry, since the predefined commercial algorithm failed to generate satisfactory results when used to generate the SNA groups for the Palestinian mobile service provider company (Jawwal), such as a low capture rate (only 55%), and failed to even capture high value customers generating and receiving hundreds of calls and SMS's. In addition to customizing the SNA algorithm for the telecom industry, relation strength and extenders have been used to enhance results in this paper. In order to reach the finest telecom SNA model, oracle SQL-PL/SQL software have been utilized, and various experiments have been tested based on different specific telecom parameters, such as group size, call duration, call count, and the ratio between duration and count. To test the new developed algorithm, 300 million call detailed record (CDR) for 4 million user in three consecutive months have been collected and used, and a result comparison with the IBM SNA model is added. Results for the new algorithm have increased coverage of network to be 75.9% instead of around 55% for IBM algorithm; moreover, all high value customers have included in the results for the new algorithm. We believe that this paper is relevant to track two cloud Distributed and Parallel systems

Customize Social Network Analysis for Telecommunications Companies

Social Network Analysis (SNA) is created to analyze social network data. Therefore, the main companies in the data mining filed (such as IBM, SAS, R and python) have created their own SNA algorithms. The aim of this research is to create customized SNA algorithm for telecom companies because the current algorithms were not designed just for the telecom networks, in addition when current algorithms were used for telecom many high value customer not include in final result plus results coverage just 55% from input customers, so in the new algorithm relation strength and extenders were used to enhance final results 300 million records that belong to around 4 million customers in the last three were collected from (Jawwal Telecommunications Company) as case study. The current algorithms and the new algorithm were used the same data. In this research six experiments were applied based on call duration, call count and ratio between call duration and call count, in addition two groups size were used (15 and 20), Oracle Sql-PL/SQL was used to implement algorithm. The results that approved by Jawwal were based on parameters that used in experiment number six (ratio between calls count and call duration with group size till 20 customer), it has increased the coverage of NW to be 75.9% instead of around 55% for current algorithms, in addition all high valued customers has included in results for the new algorithm, moreover algorithm have applied in Mobily in Saudi Arabia and the same positive results have been found same as Jawwal. New novelty ideas have created in this research such as, extenders this type of customers used for customer who is influencer in one group and follower in the other group. Also relation strength used to create groups and assign followers to their most related influencer; furthermore, Super Group used as new layer to connect related groups in one group and find super influencer