A quick peek at the quick-off-the-mark users of the altc2011 hashtag on Twitter…
Social connections between folk using the hashtag:
(Image generated using gephi; node size: betweenness centrality, colour – follower count)
By looking at the Twitter profile of hashtag users, finding a user’s blog (or other affiliation) URL, and running RSS feed autodiscovery over the URLs, we can generate an OPML blogroll (after a fashion) from the list of hashtagging twitter users: altc2011 hashtaggers – discovered feeds OPML blogroll
List intelligence: I looked at the lists that hashtag users are on and ranked lists by number of subscribers as well as number of hashtag users appearing on the lists.
Lists containing N numbers of people using the altc2011 hashtag:
Lists ordered by subscriber count (first number is number of people on list who’ve been an early user of altc2011 hashtag):
/kamyousaf/e-learning-uk 27 107
/kamyousaf/uk-ict-education 14 80
/mhawksey/purposed 24 42
/mhawksey/lak11 20 34
/helenwhd/e-learning 43 31
/suebecks/tech-enhanced-learning 27 27
/catherinecronin/education-elearning 17 26
/amcunningham/learning 17 26
/juliadesigns/education-uk-18 21 25
/JonPowles/education 26 19
/PatParslow/elearning-crew 15 18
/mhawksey/jiscel10 19 14
/ousefulAPI/altc2010 52 12
/ZoeEBreen/elearning-evangelists-uk 20 9
/ulcc/mootuk11-taggers 18 9
/HeyWayne/learning-tech-people 15 9
If we look at membership of lists containing altc2011 members, and then see who appears on those lists, we get an idea (maybe) of notable people in the community (number is number of lists each person appeared on):
6 thoughts on “Early Peek at ALTC2011 Twitter Community…”
What does it mean? How can I use this?
@alan What does it mean? Very little. I see it as a map of folk interested in the area, and e.g. who’s popular in terms of follower numbers.
The OPML: that can be uploaded into Google Reader and will aggregate content from feeds related to people who tweeted about ALTC2011. Whether it’s useful is an other matter; but it’s a way of automating the collection of feeds and building up a blog roll of content that presumably relates to the sort of areas that ALTC2011 covers. (I also generate Google custom search engine configuration files that define a search engine that searches over sites taggers link to from their profiles. On to do list is to add in links shared with the tag to the CSE definition.)
The lists: who knows; at the moment, lists aren’t used that much, but they do provide some sort of signal based around human curatorial effort; the list names may or may not be useful as tags to label the sort of area that ALTC2011 relates to. As to highlighting people who appear on lots of lists associated with people using the ALTC2011 hashtag, it’s possibly another signal that can be used to identify notable people in the community.
Hmm.. thinking about it, it’s load of total b****ks isn’t it? A complete waste of time… I guess at least I only drained OU resources developing this stuff, rather than sinking shed loads of public grant money into it too…
@alan on a personal level it depends how far you want to go down the gratuitous network building (you little klout chaser you ;). In that case you would look at the ALT visualisation and look for people with ‘big nodes’ who you don’t already follow. After following them a couple of carefully made RTs and they can become the bridge for expanding your own network http://www.connectedaction.net/2011/03/05/how-to-build-a-collection-of-influential-followers-in-twitter-using-social-network-analysis-and-nodexl/
On an educational level if you were using social networking in your class you could graphically see which students are influencing the network, who they are influencing, maybe spot some stragglers.
@martin Ah – you’ve started collected social media optimisation recipes, have you?! That’s something I’ve not got round to yet…. (thinks… hmmm ….nope, defintely not blogged around that… yet… Race you to the first 10K views and 100 comments on that topic…? Heh heh…:-)
I’d forgotten Alan was now whoring himself for klout (and presumably peerindex?) credit points. Whilst Klout persists in in rewarding follower numbers and random amplification, a good strategy would be to tweet things that attract spam bots; maybe avoid the pr0n stuff, but maybe go for stuff around careers/jobs/life-coaching (he can pretend these are relevant to education), maybe also start tweeting about Leicester to attract local followers (again, pretending that being followed by random Leicester-based estate agents is relevant to building up a strong local profile).
Now are you sure you haven’t got something tucked away in the archives ;) That post is by one of the NodeXL leads Marc Smith. He started following me and retweeted a couple of my posts so I followed him back and had a look at his work … doh!
Alan’s also been updating his LinkedIn profile lately adding AJ Cann Consultancy. Give it a week and he’ll be sending out the follow robots ;)
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