Social network analysis (SNA)

Social network analysis (SNA)

Social network analysis is the mapping and measuring of relationships and flows between people and community. Each participant in the community is called an actor and depicted as a node.  The nodes in the network are the people and groups while the links show relationships or flows between the nodes. Social network can be represented in graphical representation – Sociogram. This network effectively shows the distinction between the three most popular individual centrality measures: Degree Centrality, Betweenness Centrality, and Closeness Centrality.


SNA Measurements



 
Above social network can be represented in a matrix:

	Alice	Bob	Carol	David	Eva
Alice	-	1	1	1	0
Bob	1	-	0	1	0
Carol	1	0	-	1	0
David	1	1	1	-	1
Eva	0	0	0	1	-

Density

The density is used to measure the closeness of a network, is an indicator for the general level of connectedness of the graph.
Density = (L/ [g(g-1) / 2]) = 2* 6/20  = 0.6


Degree Centrality

Degree centrality of a node refers to the number of edges attached to the node.

	Alice	Bob	Carol	David	Eva
Degree centrality	3	2	2	4	1

Degree centrality can be normalized as below:

	Alice	Bob	Carol	David	Eva
Normalized	0.75	0.5	0.5	1	0.25

Closeness Centrality

An actor is considered important if he/she is relatively close to all other actors. Closeness represents the mean of the geodesic distances between some particular node and all other nodes connected with in

	Alice	Bob	Carol	David	Eva
Closeness centrality	0.2	0.17	0.17	0.25	0.14

Closeness centrality can be normalized as below:

	Alice	Bob	Carol	David	Eva
Normalized	0.8	0.67	0.67	1	0.57

We can find that David got the highest Closeness Centrality. He is most influential because he connected to all other nodes within the network.


Betweenness Centrality

Betweenness centrality is a measure of a node's centrality in a network equal to the number of shortest paths from all vertices to all others that pass through that node.

	Alice	Bob	Carol	David	Eva
Closeness centrality	0.5	0	0	3.5	0

Betweenness centrality can be normalized as below:

	Alice	Bob	Carol	David	Eva
Normalized	0.083	0	0	0.58	0

Result

After getting above measures for Social network analysis, we can find that David got the highest value both Degree Centrality, Closeness Centrality and Betweenness Centrality. David is the center within the social network and is the most influential one.