[Air-L] Quantifying Political Alignment

jeremy hunsinger jhuns at vt.edu
Mon Nov 22 07:55:19 PST 2010


you may want to talk to any number of political scientists that work in the field, there are several large digital analysis projects going on in political science that you can find by looking at the NSF grants in the field from 2006.   There problem frequently faced is that it is very hard, even with normalized texts, to get more than 90% reliability in computer coding, some have managed to get up to 96%, but that 4% can really throw analysis for a loop.  I don't think there is an established metric, there are contested ways of coding texts which one person or another might defend, but here:  http://enapt.org/bibliography/   is a good place to start your research.  
On Nov 22, 2010, at 10:36 AM, Michael Conover wrote:

> Our research group (made up of physicists and computer scientists) needs to
> evaluate the political content of short pieces of text.  To this end we've
> constructed a rubric for classification, ranging from strong left, lean
> left, and neutral, to lean right, strong right, and unclassifiable.  While
> the criteria of the rubric are rather clear cut (a 'strong' classified
> sentence would contain attacks on a person or group's character, hyperbolic
> language, or intense / fanatical expressions of support for an issue), we
> all suspect that this is a solved problem.
> 
> I've heard this referred to by political scientists as 'coding' text, and it
> definitely falls within the domain of qualitative content analysis, but I'm
> yet to find anything specifically on evaluating political text.  This in
> mind, can anyone point me towards an established metric for evaluating the
> political content of bodies of text?
> 
> Thanks kindly,
> Michael Conover
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Jeremy Hunsinger
Center for Digital Discourse and Culture
Political Science
Virginia Tech



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