Few days ago Axle Burns and the people from “Mapping online publics” posted a very interesting article about mapping the Australian election following #ausvote tweets. The idea behind that was rather good and simple: by mapping all the messages containing the conventional reply symbol (@username) one could map the conversational network surrounding a specific topic (defined by the #hashtag). Of course this methods has some limitations (clearly explained by Axle), nevertheless it can be use to produce a rough map of the conversational network.
Since some time ago we’ve downloaded (using Twapperkeeper – the same service used by Axel) all the tweets with the hashtag #ukge2010 (the “official” hashtag about Uk general elections) we have decided to do the same analysis on Uk tweets.
So we’ve got the @replies network and using gephi we counted the indegree and the betweenness centrality of the nodes. Following Axle we’ve also excluded from the visualisation itself any users who received fewer than 100 @replies.
Here you can see the result:
The size of the nodes represents the indegree value while the colour represents the betweenness centrality. This is the table showing the top values:
What can be easily noticed is that most important nodes within the conversational network are not the official twitter account from political parties or politicians. Bloggers, journalists and consultants like @carlmaxim or @bengoldacre get more direct replies than official twitter account from politicians – like @nick_clegg – or from political parties – like @UKLabour-.
This can be due to the use that those users make of Twitter, @nick_clegg or the @UKLabour probably are not perceived as someone you would reply or address directly.
At the same time it is important to highlight how there is no clear correlation between indegree and betweenness centrality, users like @bloggerheads have a high betweenness centrality value but a very low indegree. This can be surely due to a different behaviour of users (outdegree value is important in how betweenness centrality is defined) but at the same time I think that betweenness centrality, even if is a standard measure for sna, is unable to get the real complexity of a conversation network connected through a Twitter #hashtag (but we’re coming back on this point very soon).