Call for Papers: 4S 2007, Montreal, October 11-13 Latin American Science and Ways of Knowing Organizers: Christina Holmes Ricardo Duque Abstracts should be sent by January 30th. Scientists in Latin America face a variety of challenges contributing to global scientific knowledge. Given that scientific ways of knowing are always enacted within particular contexts this group of papers asks how challenges to producing scientific knowledge are negotiated in Latin America? This includes such factors as the mediation of language politics, as some languages are scientifically more powerful than others, the maintenance of networks, and the communication channels through which both language and networks are managed in order to create scientific knowledge within Latin America. If you are interested in participating in this panel, please contact Christina Holmes at cpholmes@dal.ca Abstracts should be sent by January 30th. --- air-l-request@listserv.aoir.org wrote:
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Today's Topics:
1. Question re Size of Data Set... (Matthew Pearson) 2. Re: Question re Size of Data Set... (Paul Teusner) 3. Conferences in Asia this spring? (Jill Walker) 4. Re: Conferences in Asia this spring? (Dominic Pinto) 5. The CIA and Facebook (John McNutt) 6. Re: The CIA and Facebook (Fred Stutzman) 7. Re: Conferences in Asia this spring? (Beth Kolko) 8. Re: internet community breakups (Marcus Foth) 9. Re: Conferences in Asia this spring? (smork@itu.dk)
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Message: 1 Date: Wed, 24 Jan 2007 15:31:44 -0800 From: Matthew Pearson <mdpearson@wisc.edu> Subject: [Air-l] Question re Size of Data Set... To: air-l@listserv.aoir.org Message-ID: <3001D11C-8CB7-42FD-BECE-9F4EA3BE2A35@wisc.edu> Content-Type: text/plain; charset=US-ASCII; delsp=yes; format=flowed
Hello All:
This is my debut post to this excellent list after a long time spent reading lots of good stuff from others.
I have a question re the size of my data set for my dissertation project: Is my data set too large, too small, or just right?
I'd very much appreciate any insight/ideas/feedback anyone has about this. My advisor and I aren't that sure about this issue, and I haven't been able to discern much about this issue from a lot of the studies I've read.
I do realize my question is thus far meaningless without knowing anything about my project, so here's some more information/background:
I'm doing a close look at one message board community--one devoted to discussion of a particular college basketball team. I've got all sorts of things I'm interested in, but my central research question has to do with the ways that people teach each other and learn from one another the conventions for discourse in/on the message board. (I'm also interested in potential emerging genres of writing, the influence of sports fandom on online literacy practices, and perhaps even examining issues related to gender (which I realize is a pretty general thing to say, but I'll keep it at that for now).)
I've got two main sources of data: both (1) archived threads/posts from the message board, and (2) online questionnaires that participants/members filled out. My question concerns source (1)-- the archival data.
I have tons of data archived. I used one of those "site-sucker" programs to grab all the discussions on the message board over about a 8 month period of time. Given that this message board is a pretty busy one and that I'm using a ground-theory approach to the data analysis, I chose to sample a smaller set of the overall data. I used an "event sampling" method and, with input from posters on the message board, chose 5 "big" events around which to sample discussion. I then also chose 5 other events that occurred during the months I archived discussion that were not listed as "big" events by anyone who offered their sense of the "big" events. I didn't, though, choose just those threads of discussion related to those "big" and non-big events, but rather used those as anchoring moments in time, and then sampled ALL discussion that occurred on those dates, and one day prior and one day later. This resulted in such a large data set that I ended up using only 3 "big" events and 3 non- big ones, and then sampling for those dates, and the days immediately around them.
What I'm left with now is about 4000 individual .html pages, some of which have fairly detailed threads of discussion, with sizable individual posts, and also, of course, many of which that have cursory, short sentences that perhaps look more like "chat." This is a lot of stuff to wade through, yet it does represent only 18 days of life on this message board. Thus far I've been going through the data in separate "passes," looking for answers to particular aspects of my research question, and it's a daunting thing. I know research takes a lot of work and time, but I thought it wise to get feedback to see if I'm going overboard here.
So does my sample sound reasonable? I'm well aware that the way I sample will directly impact the kinds of conclusions can draw and level of rigor folks see in my work.
Any thoughts? Good sources re this kind of methodology? I've got Virtual Methods Ed. by Hine, among other sources, and haven't seen anything yet re sample size. Maybe I missed it somehow?
many thanks,
Matthew Pearson mdpearson@wisc.edu PhD Candidate, University of Wisconsin Department of English-- Composition and Rhetoric; Research Assistant, UC-Irvine Writing Project; & Man on the Street
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Message: 2 Date: Thu, 25 Jan 2007 10:47:53 +1100 From: "Paul Teusner" <paul.teusner@rmit.edu.au> Subject: Re: [Air-l] Question re Size of Data Set... To: <air-l@listserv.aoir.org> Message-ID: <001a01c74012$114cbfe0$6400a8c0@Paul> Keywords: Study Content-Type: text/plain; charset="us-ascii"
Hey Matthew,
I'm a PhD student too and I'm going through exactly the same problem.
For me the question isn't so much about the amount of data but how are you going to use it. How in depth is your analysis going to
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