I need some advice here.
I am starting a new article and I am looking at various sampling methods. The article will examine audience design over three different weblog communities of practice – an activist community, an academic community, and a knitting community. I have always used snowball sampling (half mined by a script, half by hand), but I wonder if that is not overkill for this much more qualitative article. For this article, I was thinking about using a stratified sampling method where I define the affordances/qualifications for the different communities of practice, then randomly pick 4-6 from each of the three groups. I thought about having both group and individual blogs, but actually having only individual blogs may give a clearer picture as it would eliminate more of the ‘talking amongst ourselves-ness’ of a group blog. Of course, that would have to be acknowledged in the article. The hypothesis of this article is that there are differences in the conceptualization and addressing of community members that are not accounted for by the affordances of the weblog tool – rather they are negotiated together with community members. So my question, dear readers, is about the validity of the sampling method. Can one make generalizations (even hedged ones) from such a small sample size?
This site is one researcher's wanderings through participatory media. Focusing on youth created media, I will use this blog to document my study of YouTube and related video hosting sites.
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So, the trick is to make sure you can say that the differences represent differences in the communities and not just individual differences between your different samples? hmmmm
Can you link the samples to the general populations of the three diff communities somehow? Like, instead of random, purposefully pick ones that you know are representative of the population? but then you’d have to demonstrate how you know somehow…
January 27th, 2010
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