It’s the last day of the OER Visualisation Project and this is my penultimate ‘official’ post. Having spent 40 days unlocking some of the data around the OER Programme there are more things I’d like to do with the data, some loose ends in terms of how-to’s I still want to document and some ideas I want to revisit. In the meantime here are some of the outputs from my last task, looking at the #ukoer hashtag community. This follows on from day 37 when I looked at ‘the heart of #ukoer’, this time looking at some of the data pumping through the veins of UKOER. It’s worth noting that the information I’m going to present is a snapshot of OER activity, only looking at a partial archive of information tweeted using the #ukoer hashtag from April 2009 to the beginning of January 2012, but hopefully gives you an sense of what is going on.
The heart revisited
I revisited the heart after I read Tony Hirst’s What is the Potential Audience Size for a Hashtag Community?. In the original heart nodes were sized using ‘betweenness centrality’ which is a social network metric to identify nodes which are community bridges, nodes which provide a pathway to other parts of the community. When calculating betweenness centrality on a friendship network it takes no account of how much that person may have contributed. So for example someone like John Robertson (@KavuBob) was originally ranked has having the 20th highest betweenness centrality in the #ukoer hashtag community, while JISC Digital Media (@jiscdigital) is ranked 3rd. But if you look at how many tweets John has contributed (n.438) compared to JISC Digital Media (n.2) isn’t John’s potential ‘bridging’ ability higher?
[In the bottom left you’ll notice I’ve included a list of top community contributors (based on weighted betweenness – a small reward for those people (I was all out of #ukoer t-shirts).]
These slides also show the difference in weighted betweenness centrality (embedded below). You should ignore the change in colour palette, the node text size is depicting betweenness centrality weight [Google presentation has come on a lot recently – worth a look at if you are sick of the clutter of slideshare]:
The ‘pulse’ of #ukoer
In previous work I’ve explored visualising Twitter conversations using my TAGSExplorer. Because of the way I reconstructed the #ukoer twitter archive (a story for another day) it’s compatible with this tool so you can see and explorer the #ukoer archive of the 8300 tweets I’ve saved here. One of the problems I’m finding with this tool is it takes a while to get the data from the Google Spreadsheet for big archives.
Is there still a pulse?
The good news is there is still a pulse within #ukoer, or more accurately lots of individual pulses. The screenshot to the right is an extract from this Google Spreadsheet of #UKOER. As well as including 8,300 tweets from #ukoer it also lists the twitter accounts that have used this tag. On this sheet are sparklines indicating the number of tweets in the archive they’ve made and when. At the top of the list you can see some strong pulses from UKOER, xpert_project and KavuBob. You can also see others just beginning or ending their ukoer journey.
The good news is the #ukoer hashtag community is going strong December 2011 having the most tweets in one month and the number of unique Twitter accounts using the tag has probably by now tipped over the 1,000 mark.
There is more for you to explore in this spreadsheet but alas I have a final post to write so you’ll have to be your own guide. Leave a comment if you find anything interesting or have any questions
[If you would like so explorer both the ‘heart’ and ‘pulse’ graphs more closely I’ve upload them to my installation of Raphaël Velt’s Gexf-JS Viewer (it can take 60 seconds to render the data). This also means the .gexf files are available for download:]