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Can we calculate party affiliation? (The Westminster edition)

Friday, February 13th, 2009

This is a follow-up post to Why doesn’t the Tory MP have Twitter friends? — a report on some early research into the interrelationships between the few Westminster MPs who are on Twitter.

According to Tweetminster, the number of UK MPs on Twitter has doubled since this time last month. Where there were eight Twittering MPs, there are now sixteen. Here’s the map that shows who follows whom (the labels may be too small to read — if you want to see a larger image, click on the map.

I’ve coloured each node to show party affiliation; for those of you who are unfamiliar with British politics, Labour (our left-of-centre party) shows up in red, Conservatives (our right-of-centre party) in blue, and Liberal Democrats (what it says on the tin) in yellow.

The size of each node represents the individual’s “betweenness centrality” — a network analysis term that helps us place a value on individuals within a network. To give you a sense of what it means, the higher the betweenness centrality of an individual, the greater the impact when you take them out of the network. For those of you who work in large companies, it may be worth noting that senior management’s personal assistants generally have very high betweenness — something that is mostly remarked upon when they go on holiday (simultaneous translation: “take a vacation”.)

So far so good. By now, regular readers will probably be kissing their teeth and thinking “so what?” I’ve done a lot of these Twitter maps in the past and the novelty must be wearing off on you by now.

So here’s the thing. There are a few network analysis techniques that let one identify cliques and factions. What we’ve got here is a small set where we already know what people’s affiliations should be. How interesting, I thought, would it be to see how well the calculated result fits the real world data? Here’s what I found:
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