Chatham House and the Institute of Iranian Studies at St. Andrews have published a preliminary analysis of the recent election in Iran. The paper (though it is based on official stats) suggests that the election was indeed rigged to a considerable degree. Here is the complete analysis of the Iranian Presidential Election 2009.

Continue reading “Analysis of Voting Figures in the 2009 Iranian Presidential Election” »

I kid you not: yesterday the Daily Mail, not normally a promoter of civic education, published a Venn diagram outlining the overlap between the three main parties’ proposals for dealing with the parliamentary expenses mess. As diagrams go, this was not exactly brilliant. A lot of colour and space were wasted to illustrate the fact that while each party has its own preferences, they could possibly agree on a set of four or five measures. And no, because the font size was large and time was short, they did not pay any attention to proposals supported by say the Conservatives and the Liberals which are opposed by labour.

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Worldwide mutual citations in Political Science

Last Saturday, we presented our ongoing work on collaboration and citation networks in Political Science at the
4th UK Network conference held at the University of Greenwich. For this conference, we created a presentation on Knowledge Networks in European Political Science that summarises most of our findings on political science in Britain and Germany and provides some additional international context. The picture on the right shows a subnetwork of about 320 scientists who mutually cite each others’ work. Watch out for the dense IR/methods cluster and the lack of (mutual) connections between the dispersed political sociology and formal methods camps.

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Our project on social (citation and collaboration) networks in British and German political science involves networks with hundreds and thousands of nodes (scientists and articles). At the moment, our data come from the Social Science Citation Index (part of the ISI web of knowledge), and we use a bundle of rather eclectic (erratic?) scripts written in Perl to convert the ISI records into something that programs like Pajek or Stata can read. Some canned solutions (Wos2pajek, network workbench, bibexcel) are available for free, but I was not aware of them when I started this project, did not manage to install them properly, or was not happy with the results. Perl is the Swiss Army Chainsaw (TM) for data pre-processing, incredibly powerful (my scripts are typically less than 50 lines, and I am not an efficient programmer), and every time I want to do something in a slightly different way (i.e. I spot a bug), all I have to do is to change a few lines in the scripts.
After trying a lot of other programs available on the internet, we have chosen Pajek for doing the analyses and producing those intriguing graphs of cliques and inner circles in Political Science. Pajek is closed source but free for non-commercial use and runs on Windows or (via wine) Linux. It is very fast, can (unlike many other programs) easily handle very large networks, produces decent graphs and does many standard analyses. Its user interface may be slightly less than straightforward but I got used to it rather quickly, and it even has basic scripting capacities.

The Missing Manual

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More preliminary findings on Social Networks in Political Science: from our analysis of collaboration patterns in the British Journal of Political Science (BJPS) and Political Studies (PS), we conclude that co-publication is much more widespread and intense than in Germany (not a huge surprise). Yet, at least on the basis of these two journals, collaboration networks in British political science look rather fragile when compared to the sciences. Obviously, further research is needed.

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Like most social scientists I am a little bit obsessed with social networks. I’m also interested in the sociology of knowledge, which is a little more original. So some time ago, a colleague and I embarked on a project called “Networks in Political Science”, which rather unsurprisingly tries to apply network analysis to publications in Political Science. Our basic idea is that everyone seems to take subfields, theoretical schools and even citation circles for granted, but unlike in some other disciplines, little empirical work has been done so far. More specifically, we want to identify

• highly cited articles that form the core of subfields
• individual influential scholars
• sub-networks of scholars that cite each other and/or collaborate frequently, thereby forming an “invisible college” and
• individuals that are able to bridge sub-discplinary divides by publishing in a whole host of subfields.

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