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This article provides a great view of connections created by clicking between science articles ...

JBollen J, Van de Sompel H, Hagberg A, Bettencourt L, Chute R, et al. (2009) Clickstream Data Yields High-Resolution Maps of Science. PLoS ONE 4(3): e4803. doi:10.1371/journal.pone.0004803

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004803


/Caroline


On Nov 2, 2012, at 2:52 AM, Jon Brassey wrote:

> ***** To join INSNA, visit http://www.insna.org *****
> Hi!
>
> I run a clinical search engine (www.tripdatabase.com) which is used by a large number of clinicians. I've recently come across the use of click analysis and I'm wondering if people can point me in the right direction for experts, papers etc.
>
> The problem/opportunity is to analyse co-clicks. So, a person might do a search for 'prostate cancer' and they then click on articles 1, 3 and 8. The person has created connections between these 3 articles. Aggregate that over millions of searches and you've got some great data. I imagine there are lots of potential uses, but two immediately spring to mind:
>
> • Visualisations - creating a diagram of these connections and allowing people to follow the connections to find new articles, related to their topic. So, it'll help browsing/serendipity!
> • Clique identification - I can't help feeling that the connections will organise themselves and that finding cliques might allow for the easy creation of clinical reviews.
> I've no idea how to start exploring this area (I have a reasonable understanding of SNA, perhaps a bit rusty). Can anyone help point me in the right direction?
>
> Best wishes
>
> jon
>
> --
>
> Jon Brassey
> TRIP Database
> http://www.tripdatabase.com
> Find evidence fast
>
>
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_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
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an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.