OUseful.Info, the blog…

Trying to find useful things to do with emerging technologies in open education

Small World? A Snapshot of How My Twitter “Friends” Follow Each Other…

I’m now following about 500 or so people on Twitter, but to what extent are they following each other? Are there any noticeable subgroups in the folk I follow, by virtue of them being highly linked to each other in the friends and following stakes?

How my twitter friends are interconnected - size is # of my friends following my friends, colour is # of my friends they follow

Each of the nodes represents one of my Twitter friends (that is, each node represents a separate person I follow on Twitter).

Node size is proportional to the number of my friends who are following other of my friends.

Node colour is proportional the the number of my friends that person is following (blue is cold – low number; red is hot – high number).

The graph is an indication of the extent to which the people I follow (that is, my friends…) is an echo chamber…

Running the Gephi “connected cpmponents” statistic, it seems that the group is pretty tightly connected… There is one noticeable separate component that contains more than a singleton, from a few accounts I followed last year…:

Partition over my twitter friends

If I look at the labels for the other separate components (not shown), they mainly correspond to people with private accounts, although there are a couple of people who are completely independent of the rest of my Twitter social circle.

The Gephi modularity class statistic, however, suggests there is a little more structure hiding in there…

My twitter network - modularity class

(This is a random algorithm, so it may give slightly different answers each time it is run…)

Let’s peek inside them…

My twitter friends - one cluster

Looks a bit educationalist to me…;-)

How about this one:

another of my twitter clusters

Hmm. Government and open data, maybe? What next…?

ANother of my twitter friend clusters...

BBC and journ hack types, with a bit of datajourn thrown in maybe?

Hmmm – the next one looks like an OU cluster:

AN OU cluster in my twitter friends

And that leaves….

Final twitter cluster

JISC, museums and libraries…

Seems about right to me:-)

PS Images produced using Gephi… Note to self: start spending a ittle more time about tidying up the presentation of some of these images…;-)

PPS for a similar exercise applied to my Facebook friends, see Getting Started With The Gephi Network Visualisation App – My Facebook Network, Part IV

Written by Tony Hirst

September 21, 2010 at 4:59 pm

Posted in Visualisation

Tagged with ,

6 Responses

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  1. Wow! your work is so impressive. I noticed some clustering when I first used Friendswheel in Facebook in 2007 see http://www.flickr.com/photos/francesbell/1340027857/in/set-72157600216505487/ I loved the fact that app was written by a (then) Y1 CS student, Thomas Fletcher.

    Frances Bell

    September 22, 2010 at 6:31 am

  2. [...] First thoughts on things that might be useful, one day… BlogAboutSearch « Small World? A Snapshot of How My Twitter “Friends” Follow Each Other… [...]

  3. How did you export your twitter contacts? I have been trying to create a gdf file from my account, but keep coming up empty handed. Any suggestions?

    Thanks,
    Brett

    Brett Dupuy

    June 27, 2011 at 8:03 pm

    • @Brett I use the tweepy Pythion library to call the Twitter API with a “single user desktop app” OAuth key (or whatever it’s called). Another approach is to use the Google Social Circle API – that’s what I use to grab friends data for my live visualisation (view source on http://ouseful.open.ac.uk/twitter/friendviz.html )

      Tony Hirst

      June 27, 2011 at 9:30 pm

  4. [...] Tell Us?, Structural Differences in Hashtag Communities: Highly Interconnected or Not?, Small World? A Snapshot of How My Twitter “Friends” Follow Each Other…,  Visualising Twitter User Timeline Activity in R, Blogging Academic Lectures, Twitter Powered [...]


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