CHAPTER 6 Social Network Analytics 

Many types of social networks exist. The most popular are undoubtedly Facebook, Twitter, Google+, and LinkedIn. However, social networks are more than that. It could be any set of nodes (also referred to as vertices) connected by edges in a particular business setting. Examples of social networks could be:

  • Web pages connected by hyperlinks
  • Email traffic between people
  • Research papers connected by citations
  • Telephone calls between customers of a telco provider
  • Banks connected by liquidity dependencies
  • Spread of illness between patients

These examples clearly illustrate that social network analytics can be applied in a wide variety of different settings.


A social network consists of both nodes (vertices) and edges. Both need to be clearly defined at the outset of the analysis. A node (vertex) could be defined as a customer (private/professional), household/family, patient, doctor, paper, author, terrorist, web page, and so forth. An edge can be defined as a friend relationship, a call, transmission of a disease, reference, and so on. Note that the edges can also be weighted based on interaction frequency, importance of information exchange, intimacy, and emotional intensity. For example, in a churn prediction setting, the edge can be weighted according to the time two customers called each other during a specific period. Social networks can be represented as a sociogram. This is illustrated in Figure 6.1, whereby ...

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