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	<title>David Stuart &#187; social network analysis</title>
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		<title>Twitter Network Analysis: Tweetminster</title>
		<link>http://www.davidstuart.co.uk/blog/2009/10/twitter-network-analysis-tweetminster/</link>
		<comments>http://www.davidstuart.co.uk/blog/2009/10/twitter-network-analysis-tweetminster/#comments</comments>
		<pubDate>Tue, 06 Oct 2009 21:16:26 +0000</pubDate>
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				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[link analysis]]></category>
		<category><![CDATA[social network analysis]]></category>
		<category><![CDATA[Twitter]]></category>

		<guid isPermaLink="false">http://www.davidstuart.co.uk/blog/?p=111</guid>
		<description><![CDATA[In my previous post I looked at measuring Twitter impact by comparing actual number of followers with expected number of followers based on &#8216;following&#8217; and &#8216;updates&#8217;. Whilst that provides a simple means of analysis, Twitter is a social network site and (where possible) should be view at the network level. This post uses social network [...]]]></description>
			<content:encoded><![CDATA[<p>In my <a href="http://www.davidstuart.co.uk/blog/2009/09/how-many-twitter-followers-should-you-have/">previous post</a> I looked at measuring Twitter impact by comparing actual number of followers with expected number of followers based on &#8216;following&#8217; and &#8216;updates&#8217;. Whilst that provides a simple means of analysis, Twitter is a social network site and (where possible) should be view at the network level.  This post uses social network analysis techniques to investigate the interlinking of <a href="http://tweetminster.co.uk/">Tweetminster</a>-listed MPs on Twitter .</p>
<p>The network diagram clearly shows that MPs are as bad as the rest of us when it comes to only listening to what we want to hear. The arrows point from the follower to the friend; so the nodes with the most arrows pointing to them are the most followed. [<a href="http://www.davidstuart.co.uk/blog/wp-content/uploads/2009/10/TwitterMPs-1024x574.jpg" target="_blank">Click here</a> to see full-sized  picture].<br />
<img class="alignnone size-large wp-image-112" title="TwitterMPs" src="http://www.davidstuart.co.uk/blog/wp-content/uploads/2009/10/TwitterMPs-1024x574.jpg" alt="TwitterMPs" width="421" height="234" /><br />
Each of the nodes in the above diagram represents an MP, coloured according to party affiliation (those MPs that are not in one of the three main parties are coded white).  The layout of the nodes is based on the <a href="http://en.wikipedia.org/wiki/Force-based_algorithms">Fruchterman-Rheingold algorithm</a>, which tries to place connected sites close together. Party affiliation plays no part in the positioning of the nodes, although it obviously plays a part in who MPs listen to on Twitter.</p>
<p><strong>So who is the MPs&#8217; MP on Twitter?</strong></p>
<p>Whether taking into consideration neighbouring connections, or looking at the network as a whole, the most <a href="http://en.wikipedia.org/wiki/Centrality">central</a> MPs are all Labour MPs. This is hardly surprising with such a large number of Labour MPs and the tendency for party links.</p>
<p>Degree Centrality (i.e., only taking into consideration neighbouring MPs):</p>
<ol>
<li>Kerry McCarthy (<a href="http://twitter.com/@KerryMP">@KerryMP</a>) -33 MP followers</li>
<li>Tom Watson (@tom_watson) -30 MP followers</li>
<li>Sadiq Khan (@SadiqKhan) -27 MP followers</li>
<li>Kevin Brennen (@KevinBrennanMP) -26 MP followers</li>
<li>Jim Knight (@jimknightmp) and John Prescott (@JohnPrescott) &#8211; both 25 MP followers</li>
</ol>
<p>Betweenness Centrality (based on the shortest paths between all the different nodes):</p>
<ol>
<li>Kerry McCarthy (<a href="http://twitter.com/@KerryMP">@KerryMP</a>)</li>
<li>Tom Watson (@tom_watson)</li>
<li>Jim Knight (@jimknightmp)</li>
<li>Tom Harris (@TomHarrisMP)</li>
<li>John Prescott (@JohnPrescott)</li>
</ol>
<p>Obviously this network analysis has only looked at the MPs in isolation, and we&#8217;d hope it was also being used to communicate more effectively with constituents, but as with all social media metrics they are the starting point for the discussion. The next stage is looking out how the networks are actually being used to share information, i.e., through RTs, rather than just potential avenues for sharing information.  Unfortunately we have to wait a bit longer for the API to gain that <a href="http://apiwiki.twitter.com/Twitter-REST-API-Method%3A-statuses-retweets_of_me">functionality</a>.</p>
<p>UPDATE October 7th: Curiously enough I just received an email highlighting another study of the political Twittersphere by <a href="http://blog.sysomos.com/2009/10/07/exploring-the-political-twittersphere/">Sysomos</a>&#8230;curious because I was emailed at <a href="http://blog.webometrics.org.uk/">my other blog</a> which had nothing about the political blogosphere!</p>
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