Space is hard

I’ve been writing up the methodology section of my PhD, and in what is becoming a recurring theme in writing things up it’s caused me to go back over some things I read ages ago and get a fresh perspective on them.

Today that fresh perspective is about what everybody else has been doing in hyperlocal research, and where what I’ve been doing is different.

One of the things I’ve done differently in my work is embed myself for a while in organisations, which puts me inside the space and time reference of hyperlocal media workers and their practice. Most of my contemporaries are working the other way around: bringing the hyperlocal media people into their own timelines. And it turns out that what I did was hard, but valuable.

What am I talking about? OK, so a lot of hyperlocal media research is desk based. Some work has counted things — websites, articles, comments, that sort of thing — and that’s cool, because we can find out a lot by counting things. The most important thing about counting stuff is we can see how much of it there is and if there’s a lot (there is quite a bit of hyperlocal stuff as it goes) then people are happy for us to go find out more stuff.

Some researchers have found out some of the extra stuff by doing questionnaires and surveys, and that’s desk based too. All the desk based stuff is hard graft (there’s lots of data to get, then sort, and code) but it’s work that researchers can easily control.

In some projects the researchers wanted to get some richer data and they spoke to practitioners — normally using semi-structured interviews. Those interviews belong to a world that the researcher can control, too. Sure there’s a little bit of compromise in finding time that suits researcher and interviewee, but fundamentally this takes the subject out of their world and drops them into research-land.

So what have I done again? Well as I say, I went into the organisations and I made things and I observed and did some interviews prompted by the things happening around us that day (very loosely semi-structured as I had certain beats I wanted to hit).

And it turns out that space is hard — finding the space for this sort of research into hyperlocal is hard.

Because the thing is that hyperlocal media work isn’t very neat. Now truthfully no media work is. We’d be naive to think that a local newspaper journalist works a 9-5 day but there are core office hours and there’s an office so we could do participant observation of a newsroom quite easily. Hyperlocal though is rarely that neat. While there are some operations that have core hours and proper offices, a lot of the work isn’t like that at all.

So how do you deal with getting into the space and time frame of work that happens when it can, that happens on odd days, or in the gaps between things, or that happens at ten o’clock at night sat up in bed?

You can’t that easily. You definitely aren’t getting into that bed. But you can find some of the gaps and be there for them and that is really interesting.

Cleaning up Twitter data in Excel for analysis

A lot of academic work that draws on tweets as primary data will use hashtag archives as the basis of their study. What’s nice about that is that you can use tools that capture data and present them to you in a usable manner (e.g. a CSV file). If you’re doing something a little different, like reviewing tweets from a group of individuals, that’s a little harder.
I’ve been working with my BCU colleague Inger-Lise Bore on some research into fan fiction written on Twitter (it started with this blog post – we’re presenting it at MeCCSA 2011 tomorrow). There’s no hashtag used to label the tweets we want to study – we were looking instead at the entire output from a few dozen tweets. We found a few web services that promised ways of capturing and archiving this type of Twitter data for us, but they didn’t work. At all. So instead we had to use some pretty unsophisticated means to grab the data.  Continue reading Cleaning up Twitter data in Excel for analysis