## 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.