- Degree Centrality: counting the number of link, i.e., how many people can a particular person like directly. In- and out- link are counted as the same in the degree centrality. If every node in a network has both in- and out-link, we call that fully connected network. Clique means that every node connects to every other node in a network. If a network is not "clique", there must have some bridges between unconnected directly nodes.
- Between Centrality: How likely is a node to be in the direct route between two nodes
- Closeness Centrality: the distance of a node to link to all other nodes in a network
- Eigenvector centrality: How well is a person's network overall. It bases on the influence of nodes to assign score of each node.
In addition to centrality, we can use size to measure a network, calculating the number of nodes in a network. Through diameter, which is the longest shortest path of the entire network, we can see how big a network is and what the distance among nodes. Reciprocity is another aspect to interpret a network by directionality and clustering coefficient. The higher clustering coefficient, the more density of network (more connection). Nodes that are similar to each other tend to connect to each other, that is, people connect to the same person are more likely to connect to each other in the future.
To learn how to analyze social network, we can start from analyze our own personal Facebook network using the netvizz app on Facebook. Then we can use Gephi (a network analysis tool, download here) to visiulize our personal network, following the quick start guide. You will be able to see the similar graph like below. Different colors represent different communities in a group.
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| Eller MBA Facebook Network |
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