[Air-L] What kind of data do you content analyze?
luishestres at gmail.com
Thu Aug 9 18:43:17 PDT 2012
I am planning a content analysis of emails from climate change and environmental organizations, part of which will involve coding for the presence of certain climate-related frames. Just last night I handed in a proposal to that effect as part of an digital research methods class. One of the methods I considered was some sort of automated text analysis but given the relatively small sample--no more than 500 emails--I decided to go with a traditional content analysis instead.
Hope that helps,
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Luis E. Hestres
Ph.D. student | School of Communication | American University
More about me at luishestres.com
On Aug 9, 2012, at 9:22 PM, Kevin G Crowston <crowston at syr.edu> wrote:
> My research group is working on a tool to apply natural language processing technology to content analyze large volumes of text. Our initial use case is looking for evidence of various group processes reflected in email messages of online groups (e.g., showing appreciation). However, we want to the tool to be generally useful and so are planning to extend the tool to handle other kinds of texts. We spent some time discussing what a reasonable next target would be (e.g., generic text files, web-based discussion groups, tweets), but I thought I should solicit opinions from other researchers. Hence the question: what kind of data are you content analyzing?
> Kevin Crowston
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