Social Network Analysis (SNA) for Churn Mitigation/Detection: Introduction and Metrics

Social Network Analysis (SNA) for Churn Mitigation/Detection: Introduction and Metrics

DOI: 10.4018/978-1-4666-6288-9.ch004
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Abstract

Social network analysis is intentionally covered in a separate chapter for two reasons. First, the importance of this method has rapidly increased in past few years, and second, there are very few useable studies that cover social network analysis concepts in churn management. By understanding the methods explained in Chapter 3 and combining them with knowledge of SNA concepts, the analysts (readers) can unlock the full potential of advanced analytics in one of the most important fields of research today, customer relationship and especially churn analysis. With the ability to understand how those metrics can be used, integration of those methods into more complex environments is explained regarding the key topic, churn management.
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4.1 Introduction To Social Network Analysis

“All the world's a network,” William Shakespeare would surely conclude if he were a modern scientist, and John Donne would readily continue: “No man is an island entire of itself...any man's death diminishes me, because I am involved in a network...”, and they would both start following the direction of the rapidly growing number of contemporary scientist and analysts from fields as different as biology and mathematics, sociology and physics, or geography and psychology. This direction is characterized by the network way of thinking and perceiving the world around us in terms of numberless interconnected entities forming networks of different densities, shapes, and sizes. All types of relations, those among people or animals, their movements and interactions, virtual relations and links, and even relations among genes and neurons, or protein reactions in human body can be perceived as different types of networks functioning in a similar way, and therefore analyzed using same tools and models.

However, to be able to understand full complexity of the social network analysis (SNA), we shall start by defining general concept and component parts. Social network is formally defined as a group of interconnected individuals. These individuals are connected by one or more types of relations whose patterns occupy the attention of scientists and researchers. They relate to each other by either some kind of cooperation, or competition/conflict, and are referred to as entities or actors. Their relations can be depicted by a graph in which each entity (actor or individual) is depicted as what is in graph theory called a node, and their relations are depicted as links (ties). In terms of social network analysis, actors can be any sets of related entities, whereby entities need not be only persons - the scope of analyzing social networks also includes animals, genomes, and even inanimate systems, such as traffic lines and electric power grids.

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