6.1 Centrality and Centralization: An Overview

When we consider the importance of a node in a social network, how central it is usually an important consideration. In Week 4, we were able to use sociograms to identify central nodes in a network. How can we identify those central nodes mathematically in case they are not easily visually identifiable?

Centrality is a key measure in SNA developed to achieve this goal. SNA researchers have developed many ways to quantify centrality in a network. Below, I curate a list of quality resources for you to explore different centrality measures. I selected these resources because of varied ways they present centralities – equations vs. intuitions, real-world examples vs. toy networks, step-by-step demonstrations vs. one-step computation.

First, review the following PDF presentation presenting four main centrality measures: Degree Centrality, Betweenness Centrality, Closeness Centrality, and Eigenvector Centrality. Note that the author introduces node-level centrality and network-level centralization together in this presentation. These two concepts are often mistakenly treated as the same by researchers. Now you see their differences and connections. Also, if you could follow the math equations, that would be great; if not, please focus on the intuitions.

Second, watch the following video from Lada Adamic covering Degree Centrality, Betweenness Centrality, and Closeness Centrality with concrete examples. She also made an attempt to distinguish centralities from centralization. She also noted that when considering centrality, it is very important to be clear about the scope, or the boundary like we discussed in Week 4. A little tweak will make a difference.