A Brief Introduction to SNA

Social network analysis (SNA) is often confused with social networking and social media (it doesn't help that the movie about Facebook was called "The Social Network"). However, SNA has been around at least since the early 1930s. What is it? Briefly, it's a collection of theories and methods that assume the behavior of actors is profoundly affected their ties to others and the networks in which they are located (see "Networks and Religion: What is Social Network Analysis? (Probably Not What You Think)"). A very helpful (and brief) article is by Stephen Borgatti, Ajay Mehra, Daniel Brass, and Giuseppe Labianca, "Network Analysis in the Social Sciences," which appeared in Science in 2009.

In this section you will find a series of "labs" that introduce you to the basics of social network analysis (SNA). The first four function as an introduction to network data and manipulation. The first (SNA Basics #1) explores one-mode networks; the second (SNA Basics #2) introduces two-mode networks; the third (SNA Basics #3) how to simplify networks; and the fourth (SNA Basics #4) how to work with multiple networks. The next six introduce readers to various metrics and algorithms that social network analysts frequently use explore different aspects of social networks: network topography (SNA Basics #5), subgroup detection (SNA Basics #6), centrality and power (SNA Basics #7), centrality and prestige (SNA Basics #8), brokers and bridges (SNA Basics #9), and structural equivalence (SNA Basics #10).

 

To the right of each lab, you will find a link to Dropbox from where you can download the data. Each set of labs includes two documents: one containing instructions for UCINET and Pajek and one containing instructions for R. Subsequent sections will include "labs" that illustrate the analyses unique to those chapters. As with this section, in some cases the data used for the exercises will differ from the data used in the book because the latter are not publicly available. 

Errata

None noted so far.

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