

Researchers comb search logs to learn where users get stuck - frossie
http://arstechnica.com/science/news/2009/06/researchers-comb-search-logs-to-learn-where-users-get-stuck.ars

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frossie
I find this very interesting. I think personally I tend to do two kind of
searches - ones that I know in advance will only take one search, either
because I am using the search as a lazy resolver (say because I type "BBC"
knowing that google will return me a link to news.bbc.co.uk near the top, thus
saving me a bunch of typing) or because the results will steer me to a
definitive site (eg, if I type "tethering" I expect the Wikipedia page will
crop up high, and I can figure out what it is [aside: why did we need a new
term for modem?]).

The second kind of searches I seemed to do are the ones that really go quite
deep, either because the information is hard to get, or because it is complex
enough that I need to combine data from different sources, or because, as they
say, I have phrased my query poorly and need to iterate to figure out what the
magic words are.

I would be interested to know whether this is typical (ie the ditribution is
bi-modal as I described) or just of descending frequency (ie most searches end
in 1 query, the next most frequent searches end in 2, then 3 and so on)

