Social network analysis (SNA) is the analysis of social communication through network and graph theory. Here the application of SNA has been explored in telecommunication domain. Telecom data consist of Customer data and Call Detail Data (CDR). The proposed work, considers the attributes of call detail data and customer data as different relationship types to model our Multi-relational Telecommunication social network. Typical work on social network analysis includes the discovery of group of customers who shares similar properties. A new challenge is the mining of hidden communities on such heterogeneous social networks, to group the customers as churners and non-churners in Telecommunication social network. After the analysis of the available data we constructed a Weights Multi-relational Social Network, in which each relation carry a different weight, representing how close two customers are with one another. The centrality measures depict the intensity of the customer closeness, hence we can determine the customer who influence the other customer to churn.
Social Networks are the most important way to obtain valuable information in marketing, like communities, or influencers. All those interesting aspects may be useful for Community Managers, or for Marketing Campaign design, targeting the products to the right sets of people in the Social Network.Social Networks carry a lot of information, either open and transparent or under the cover and coded. Criminal organizations may use Social networks to communicate under codes, and analyzing those codes may be important.The spread of illnesses in the form of epidemics can be detected by the way that people spread the word of illnesses in the social networks. Making sensitivity analysis of such may be important to understand when and where epidemics are spreading.It is important to understand that Social Networks are regulating the way that people think of other people. Using Social Networks may be crucial to understand the way that other people trust and how much they trust on other individuals, in many situations, mainly, pro
