[Air-L] What kind of data do you content analyze?

[John McAuley]

Hi Kevin,

I'd be interested using such as tool to analyse the "maintenance work" that
is done in a social media community. I conducted a study, using manual
content analysis, on comments in a large scale online community.  I was
attempting to categorise the sort of work that is done in the community,
to maintain social order and ensure the community remains both an
interesting and friendly place for new and existing users.  We manually
coded a sample set of comments, and developed a taxonomy. I was hoping to
advance this work using text analytics to address the entire dataset, as, I
imagine, the coded comments could be used as a training set.

Let me know if this is along the lines of what you are thinking.

Rgds,

j

On 10 August 2012 02:22, 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
> Syracuse University                                     Phone:  +1 (315)
> 443-1676
> School of Information Studies                   Fax:    +1 (815) 550-2155
> 348 Hinds Hall                                          Web:
> http://crowston.syr.edu/
> Syracuse, NY   13244-4100   USA
>
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-- 
John McAuley
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Knowledge & Data Engineering Group
Trinity College Dublin
Ireland
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