In the last three lectures, Pro. Chan demonstrated
the definition of SNA. Social Network Analysis is the study of the pattern of
interaction between actors, which is simplified as SNA. In SNA, Social network
is formally defined as a set of social actors, or nodes, members that are
connected by one or more types of relations.
We must admit that the mathematics is used
for all kinds of areas. The knowledge of matrix is used for SNA to calculate
some indexes to represent the features of a social network.
The matrix used in social network analysis
is called the adjacency matrix or sociomatrix. The sociomatrix is applied to
represent the interaction among all actors. Of course, according to the
lecture, the same social network can be explained by several means, such as the
matrix, relation graph or table. I will give the example to show different
explanation means represent the same social network.
1、Matrix representation:
2、Graph representation:
3、Table representation:
In the lecture, Pro. Chan gave us two
indexes of centrality and prestige. The centrality and the prestige are used to
elaborate the actor’s interaction, importance and other features. As Pro. Chan
said, actors with centrality are those that are extensively involved in
relationships with other actors. Here the relationship with other actors is
emphasized. Also, actor with prestige is the one who is the recipient of
extensive ties. Here the recipient is emphasized. These are used to
distinguished the concepts between the centrality and the prestige. And
centrality contains degree centrality, closeness centrality and betweenness
centrality. Prestige contains degree prestige, proximity prestige and rank
prestige.
Usually a social network’s relationship
graph can be converted into a matrix. And the centrality index and the prestige
index can be worked out according to the matrix and some formulas. And then we
can judge the features according to these values.




