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DataNinjas = read.csv(“software.csv”, head=T, sep=”;”, na.strings=na) (1)

So, now you’ve caught up with the basics of SNA you’re just dying to try it yourself, right?!ucinet tutorial network analysis tools warning
Alright!
Now, the next step is finding the right software.

BE WARNED though!

If you’re thinking: ‘Yes! I’ll just dump my data in the first program they mention, tap a few buttons and all secrets will be revealed’, you’re seriously mistaken. The computer does not solve your research questions for you. If it were that easy, we’d all be out on the streets begging for a job. You can let the computer perform all the hocus pocus you want, YOU are still going to have to interpret the results.

There, now we scared of the SNA posers, we can get down to business.

UCINET Tutorial: Why UCINET?

There’s tons of software out there to help you with your calculations, correlations, transformations, permutations, visualizations, … (here we go with the –ations again! Seriously! Maybe I should make a network out of them). There are all-rounders, like UCINET, some focus more on the numbers (such as R), others (Gephi for example) are geared toward those who like fancy spaghetti monsters (guess who?!). If you’re working with really large, or even HUGE data, Pajek’s your cup of tea, although it works just as well for small networks. There’s no such thing as “the best” program to work with, although everyone probably has a favorite. Gephi is our top choice, not just because of the fancy schmancy visuals, but also because it’s very user-friendly. When it comes to metrics, however, it’s pretty limited. For those, I turn to UCINET (which is why I’m doing this UCINET tutorial obvs), while Silke gets her kicks in R. Why? No idea. The fact that she took the introduction course to SNA & R and I the equivalent for UCINET at last year’s Sunbelt in Hamburg has nothing to do with this of course.
Anywho, over the next couple of posts we’ll let you know what we think of some of the major software programs, with tips ‘n tricks to help you out. If you have any questions, Google it, for cryin’ out loud, that brain of yours is there for a reason! Just kidding, we’re happy to help if we can. Not. No really, fire away… we dare you…

UCINET Tutorial: the first steps

ucinet tutorial screenshot

When dealing with SNA, you’ll no doubt hear about UCINET sooner rather than later. This user-friendly software has plenty to offer, both for the SNA noob as well as the seasoned network enthusiast. Conversion from two-mode to one-mode, centrality measures, density, K-cores, ego networks, triad census, multidimensional scaling, QAP correlations (eum, yeah, sure, we know how to do all that) and loads more fancy buzzwords, it has it all!
If you’re a Mac aficionado like ourselves, you’ll need to set UCINET up through Winebottler; instructions can be found here. After that, it’s a peace of (rainbow) cake, promise!

ucinet tutorial network analysis tools rainbow.jpg

Or gooey chocolate if you prefer:

ucinet tutorial network analysis tools cakegooey

I myself am a huge fan of lemon merengue pie:

ucinet tutorial network analysis tools silky-tangy-lemon-meringue-pie

It’s really easy to get started in UCINET. You can create your adjacency matrix directly in the program itself, or, if your data is stored in a database, like ours in a Filemaker environment, you can extract it to Excel and then drop it all in UCINET.

ucinet tutorial network analysis tools adjacency matrix
Adjacency matrix

Unfortunately, UCINET’s import from/export to Excel function doesn’t work for Mac, but a simple copy+paste does the trick! Be careful though, since you’re working in a Windows “environment” in UCINET, cmd+c and cmd+v won’t work, it’s ctrl+c and ctrl+v!
I’ve also had some viewing troubles since updating to OS X Mavericks: sometimes the UCINET window is stuck in the lower half of our screen. No idea what triggers this, perhaps it’s hung-over from the previous session, I dunno. It’s no big deal in itself, except if you’re obsessed with computer screen feng shui, but it does become problematical when opening Netdraw, since that window is nowhere to be seen. Maybe UCINET senses some high frequency infrared extension of my screen somewhere, but I sure as hell can’t detect it. Just quit the application and reopen it if this happens, normally that should solve this little quirk (after a couple of tries…).

UCINET Tutorial: Netdraw & visualization

Netdraw is UCINET’s built-in visualization tool. You won’t create any aesthetic masterpieces with Netdraw, but it does what it’s supposed to, that is, draw networks, and since it’s linked to UCINET, you can load in all the stuff you calculated there, which is super neat!

ucinet tutorial network analysis tools netdraw
Netdraw

There’s one major (well, all actually depends on the data you’re working with) drawback to UCINET: it freaks out when dealing with large networks. I think about 3,000 nodes is the limit, it just freezes then. But have no fear, there are plenty of other programs that can deal with ginormous amounts of data. Just keep an eye out for one of our next posts…
There are UCINET Tutorial + Netdraw workshops @ Sunbelt every year (been there, done that), both for rookies and advanced users, and they are HIGHLY recommended. And very popular, so sign up early!
You can download a trial version for free and it’ll last you 90 days. After that, you’ll have to cough up $150 – $250 bucks, but there’s no restriction to the number of computers you install it on, and updates are free to infinity and beyond.
Also, here’s the link to the UCINET help index page, for if its gazillion features make you feel dizzy, to their quick start guide, and to Hanneman and Riddle’s introduction to social network methods with examples in UCINET. And finally, you can subscribe to their Yahoo group where you can bomb them with all the silly questions you want!

Next week: R in all its quirky geeky glory!

Yanne

One Comment

  1. interesting to try to follow a bit, so I'm a slightly more able to tell others what my daughter Silke is doing in fact. I then try to explain social network analysis on an even lower level and these posts are usefull to say the least. First condition to explain is to understand a bit yourself. Interesting, but lacking time to dig really into it. Yes, interested in too much things and still a tank to build. I wonder if my tanknetwork would be visualised how big and complex that would be, a bit bigger than the Potterstuff 😉

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