[Air-L] Air-L Digest, Vol 97, Issue 10
pjeter at eden.rutgers.edu
Mon Aug 13 12:28:07 PDT 2012
I'm finishing up my Master program at Rutgers University. For my capstone project I tackled markers of online identity deception by doing a content analysis of comments associated with about a dozen YouTube videos. Also, about a year ago, I did an ethnographic study of the community associated with a blog so in that case I was analyzing the content of the message boards associated with the blog.
I hope you find this helpful.
> Message: 1
> Date: Fri, 10 Aug 2012 01:22:20 +0000
> From: Kevin G Crowston <crowston at syr.edu>
> To: "air-l at listserv.aoir.org" <air-l at listserv.aoir.org>
> Subject: [Air-L] What kind of data do you content analyze?
> Message-ID: <868D227F-04A0-4C76-AD76-E0F5CD970616 at syr.edu>
> Content-Type: text/plain; charset="us-ascii"
> 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
More information about the Air-L