archives

(Cross-posted from Gatewatching.)

In a previous post, I mentioned our work in developing a new methodology for mapping link and concept networks in the Australian blogosphere. For a first test run of this project, we archived posts in some 300-400 Australian political blogs between the start of November 2007 (the last month of the federal election campaign) and the end of January 2008, and we've now begun an exploratory analysis of this corpus of data.

As noted in our discussion paper for this project, the first step in this analysis is to distinguish between different functional components of blogs and blog pages (something that does not necessarily happen in comparable studies, by the way). So, what I'm focussing on here are the blog posts themselves, which are of course the major discursive element of any blog - as part of our approach, we've separated these posts from all other content on the blog (headers, footers, blogrolls, sidebars, comments sections, etc.). While I'll mainly discuss content analysis here, this is especially important also in the context of link analysis, of course, where blogroll, comment, and other links skew the data if we want to focus on examining the discursive network between blog posts.

So, building on this corpus of blog post data, here are some preliminary observations. What I've done here in the first place is to run the concept mapping software Leximancer over the content gathered from a selection of key Australian blogs, to both fine-tune that process and see if any discernible differences between individual blogs emerge. I'll present the results in two ways: one simply lists the key terms for each blog in order of frequency (giving a quick indication of what they're frequently talking about), and the second maps these key terms in relation to one another - terms which frequently co-occur in close proximity to one another in the text are located closer to one another than terms which don't, in other words. (I'll post these maps later, in the second part of this post.)

(Crossposted from Gatewatching.)

In this second part, we'll follow on from our discussion of key themes in The Other Cheek, Larvatus Prodeo, and Club Troppo by looking at the concept maps which Leximancer produces. But first, a recap of the background for this study: I've already posted about our work in developing a new methodology for mapping link and concept networks in the Australian blogosphere. For a first test run of this project, we archived posts in some 300-400 Australian political blogs between the start of November 2007 (the last month of the federal election campaign) and the end of January 2008. We distinguish between different functional components of blogs and blog pages, and what I'm focussing on here are the blog posts themselves, which are of course the major discursive element of any blog - as part of our approach, we've separated these posts from all other content on the blog (headers, footers, blogrolls, sidebars, comments sections, etc.).

What I've done here in the first place is to run the concept mapping software Leximancer over the content gathered from a selection of key Australian blogs. In the first part of this post, I simply listed the key terms for each blog in order of frequency (giving a quick indication of what they're frequently talking about), which produced some notable differences between the three blogs. My reading of this is that Club Troppo focusses much more strongly on policy analysis over political wonkery and insider gossip; for The Other Cheek, the balance is reversed, while Larvatus Prodeo sits somewhere in the middle.

In this second part, I'll map these blogs' key terms in relation to one another - terms which frequently co-occur in close proximity to one another in the text are located closer to one another on the map than terms which don't, in other words. The resulting maps provide further support to the observation that the blogs have different points of focus in their day-to-day coverage of politics - and by plotting all frequently-used terms on the map, the exact nature of these topical clusters becomes a little clearer, too.