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?
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…:
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…
(This is a random algorithm, so it may give slightly different answers each time it is run…)
Let’s peek inside them…
Looks a bit educationalist to me…;-)
How about this one:
Hmm. Government and open data, maybe? What next…?
BBC and journ hack types, with a bit of datajourn thrown in maybe?
Hmmm – the next one looks like an OU cluster:
And that leaves….
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
6 thoughts on “Small World? A Snapshot of How My Twitter “Friends” Follow Each Other…”
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.
My Facebook friends cluster too… eg I used Netvizz to export my friends’ context from Facebook and viewed that in Gephi too…
(Note to self: play with Facebook API to see how to export this data…)
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?
@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 )
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