[openbiblio-dev] [okfn-discuss] Help needed with visualization
jcmcoppice12 at gmail.com
Wed Jan 25 09:30:25 GMT 2012
Just cc'ing the open-science list in case anyone has ideas.
On Tue, Jan 24, 2012 at 4:47 PM, Peter Murray-Rust <pm286 at cam.ac.uk> wrote:
> This is very exciting and something I have been scratching at in science
> publishing. Now the Openbiblio team has produced Bibsoup/bibserver and it
> seems your application could be very well suited to for BibSoup
> On Tue, Jan 24, 2012 at 4:25 PM, Guo Xu <digitalepourpre at gmail.com> wrote:
>> Hi folks,
>> I have been working on visualizing the networks of academic publishing
>> in economics. Here's an example for the Quarterly Journal of
>> A link indicates that two economists have published together in the
>> QJE. The strength of a link is defined by how many times they have
>> published together.
>> The size of the node indicates how many times an author has published
>> in the QJE. Bigger nodes have published more often.
>> Finally, the color indicates the ranking of the economist's alma
>> mater. Blue indicates that the author obtained his/her PhD from a top
>> 10 university (according to
>> orange indicates a top 11-20 university; green is for top 21-30 and
>> red is for all universities beyond top 30.
>> Couple of interesting points:
>> - It seems that the core (those at the centre) are almost all made up
>> by top 10 authors. They tend to be well-connected.
> In the UK this might be called "the old boy network" - the unofficial
> network of (men) who have been to the same school / university. It does not
> necessarily indicate absolute vaue but it is often correlated with getting
> grants, etc. [I have been in both Blue and Red universities (in science)]
>> - The hubs are: Phillipe Aghion, Daron Acemoglu, Marianne Bertrand
>> - There are rarely authors beyond the top 30 who get published in the QJE.
>> The visualization is done with D3. But it is very slow on older
>> computers. Does anyone have ideas for optimizing this?
> Yes. This is a dynamics exercise and (I assume) you have a pairwise
> repulsion term to spread the points out. Many of your points are
> 0-connected and so you spend a lot of time computing them for nothing.
> Unless there is some other hidden coordinate I would just separate into
> the disjoint graphs. It will be hugely fast as instead of O[N*N] you have
> O[N] or less (there is a power law distrinution of cluster size)
>> Also, I have a lot more characteristics lying around that can be
>> displayed (e.g. gender - btw only 10% of the authors are female), but
>> I do not really know how to do it dynamically.
>> Finally, I would ideally like to do the same visualization for the
>> *entire* network of economist. I have a 300 MB dataset scraped from
>> Repec that gives me information on co-authoring for virtually all
>> economics journals and working paper series. But obviously this will
>> be too slow to visualize so it would be great if someone had
>> experience in working with such big datasets (the whole dataset has
>> ~30.000 economists, which results in a 30.000 x 30.000 data matrix!!)
>> You will certainly find interest on openbiblio-dev as we are looking for
> bibliographic data sets and things to do with them
>> Anyway, let me know what you think and looking forward to suggestions!
>> okfn-discuss mailing list
>> okfn-discuss at lists.okfn.org
> Peter Murray-Rust
> Reader in Molecular Informatics
> Unilever Centre, Dep. Of Chemistry
> University of Cambridge
> CB2 1EW, UK
> okfn-discuss mailing list
> okfn-discuss at lists.okfn.org
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