social network analysis

     Social network analysis is a kind of research methods studying the relationship between a group of actors. A group of actors can be people, communities, groups, organizations, countries, etc.. The phenomenon and data reflecting from their relationship model is the focus of the network analysis. From the perspective of social network, the interaction among people expressed in social environment can be viewed as a model or rules based on the relationship, and the regular pattern based on such relationship reflects the social structure. The quantitative analysis about this structure is the starting point of social network analysis.

     In social network analysis, there are some important concepts, which include degree, closeness and centrality. With the help of these concepts, we can get more useful information through the social network.

     Degree is used to describe the number of edges connected to the vertexes in graphs. The degree of an actor can show the number of ties he has in a social network and the number of people he is connected to. Depending on this data, we   might conclude the importance of this actor among other people.

    Closeness is another important concept referring to the extent to which an actor is close to all other people in the social network. There maybe more than one path between two vertexes and we only consider the shortest one. By adding all of the shortest distance from one vertex to all other ones and inversing the answer, we get the closeness of this vertex.

    Centrality is the measure of relative importance of an actor in a social network. It can be measured by many methods. One of them called betweenness centrality is defined by the number of shortest paths in the network that pass through one vertex. Betweenness centrality can reflect the importance of an actor in a social network. If an actor with high betweenness centrality is removed, many shortest paths will be altered at the same time.

    There is a proverb which is “Will matter is not what you know, but who you know.” briefly and aptly explaining what social network analysis actually means, I think.