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types of social network analysis courses

We live in a golden age of network analysis. It’s booming as science and booming as business. This raises questions for the teacher – what course should you teach? A few options:

  1. Bare bones: A course designed for folks with little to no mathematical background. You would teach descriptive stats, visualization, and applications.
  2. Stats+/Models : In this course, you’d assume some basic background. Maybe micro for econ students or stats for other social science students. Then, you’d dig deep into different centrality measures, power laws, clustering/community detection, etc. A follow up course would deal with p*, ERGM, Sieana and other advanced issues.
  3. Programmers: Here, you’d lightly gloss over the math and proofs and instead focus on how to scrape the net for data, how to write simulations, and how to manipulate big data sets.
  4. Elite stats: This is for a very small number of students in math, stats, or econometrics. It would be exclusively proofs of fairly advanced issues (like the graph models underlying p*).

Currently, I teach a course for sociology seniors between 1 and 2. I get soc students, a handful from econ/psych/poli sci, and one or two informatics students. I also get one or two grad students. The elite soc programs, where students often have science backgrounds or simply a lot of mojo, are now seeing Programmers courses. Old school networks courses (a la Ed Laumann or John Padgett at Chicago) offer a version of #2. Elite stats is exceptionally rare in that if students are that advanced, they can often read the papers themselves. Add your own comments about networks education.

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Written by fabiorojas

September 25, 2015 at 12:01 am

Posted in education, fabio, social networks

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5 Responses

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  1. All the programming skills in the world won’t change the fact that people (to a certain degree! within certain constraints!) select into their social networks. What I would love to see is a class on designing field experiments that can credibly manipulate network structure.

    Liked by 1 person

    haastalavista

    September 25, 2015 at 12:11 am

  2. @hasta: Absolutely, that is why there is a lot of research into identification methods and network data. But still, people have to start somewhere

    Liked by 1 person

    fabiorojas

    September 25, 2015 at 4:30 pm

  3. I’ve been teaching course like this at Stanford GSB (OB622) for the last few years and it’s been fun. The body of research on network field experiments is pretty small right now, and most of the stuff with online networks (with a few recent exceptions). But I suspect that in the next few years we’ll start understanding how to do network experiments in real life better. I think the combo of great experimental data from the field + the amazing methods that the network analysts have developed + formal theory = lots of progress.

    Liked by 2 people

    Sharique

    September 25, 2015 at 5:29 pm

  4. Sad that there is nothing about network analysis as an intellectual approach. Paradigmatic. This is all technique oriented

    Liked by 1 person

    barrywellman

    October 2, 2015 at 7:58 pm

  5. Barry: Yes, I didn’t list it as a course, but networks as paradigm do now routinely appear in many soc courses. Also, I focus on technique because people need to understand the term “network” before they can intelligently discuss paradigms.

    Like

    fabiorojas

    October 2, 2015 at 8:38 pm


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