Just a quick observation inspired by the online “focus group” on Twitter yesterday around the #twitterou hashtag (a discussion for OU folk about Twitter usage): a few minutes in to the discussion, I grabbed a list of the folk who had used the tag so far (about 10 or people at the time), pulled down a list of the people they followed to construct a graph of hashtaggers->friends, and then filtered the resulting graph to show folk with node degree of 5 or more.
Because a large number of OU Twitter folk follow each other, the graph is quite dense, which means that if we take a sample of known OU users and look for people that a majority of that sample follow, we stand a reasonable chance of identifying other OU folk…
Doing a bit of List Intelligence (looking up the lists that a significant number of hashtag users were on, I identified several OU folk Twitter lists, most notably @liamgh/planetou and @guyweb/openuniversity.
Just for completeness, it’s also worth pointing out that simple community analysis of followers of a known OU person might also turn up OU clusters, e.g. as described in Digging Deeper into the Structure of My Twitter Friends Network: Librarian Spotting. I suspect if we did clique analysis on the followers, this might also identify ‘core’ members of organisational communities that could be used to seed a snowball discovery mechanism for more members of that organisation.
PS hmmm… maybe I need to do a post or two on how we might go about discovering enterprise/organisation networks/communities on Twitter…?