Social Networks Analysis (SNA) is not new; sociologists have been using it for a long time to study human relationships (sociometry), find communities, and simulate how information or a disease is spread in a population.
With the rise of social networking sites such as Facebook, Twitter, LinkedIn, and so on, the acquisition of large amounts of social network data is easier. We can use SNA to get insight about customer behavior or unknown communities. It is important to say that this is not a trivial task, and we will face sparse data and a lot of noise (meaningless data). We need to understand how to distinguish between false correlation and causation. A good start is to know our graph through visualization and statistical analysis.
Social network sites give us opportunities to ask questions that are otherwise too hard to approach, because pooling enough people is time-consuming and expensive.
In this chapter, you will learn how to get insight into the proportions...