First impressions: Google Scholar updates

Thanks to @LSEImpactBlog and Jonathan Eisen, I found out yesterday about a potentially very handy new feature in Google Scholar.

I’ve had a Google Scholar profile for some time: after all, I might as well  be wherever a potential reader might find me – and the work involved is minimal. However, I’ve been rather sceptical of its value, not least because of its persistent inability to distinguish me from an oceanographer with the same name.

However, this new Updates feature would seem to take things to a new level. The Google Scholar blog explains:

We analyze your articles (as identified in your Scholar profile), scan the entire web looking for new articles relevant to your research, and then show you the most relevant articles when you visit Scholar.  We determine relevance using a statistical model that incorporates what your work is about, the citation graph between articles, the fact that interests can change over time, and the authors you work with and cite.

Jonathan Eisen gives a very interesting account of just how useful these results seem to him, on first try, in the LSE Impact Blog. In the interest of providing more initial feedback on a new tool, I thought I’d do something similar.

Looking at the four Top Updates – those that Google thinks should be most interesting to me – it’s pretty good. One I am interested in (and indeed had already read). Two more are by Grace Davie (who I have cited extensively), but which I didn’t know of; and a fourth is by a new author to me, which looks to be of general interest. So: of four, I might read three, especially those that are available Open Access; but none for definite.

Looking then at the further five not rated as Top,  it’s a little more wobbly. One I can’t see the relevance of at all; one I think is connected to a tangential footnote in a rather elderly article of mine; the others, whilst kind-of interesting, I’m unlikely to read unless I found myself with some sabbatical leave. To be fair, my work has spanned early modern and modern periods, as well as digital resources and Open Access publishing, and so that diversity presumably presents difficulties to a model that is trying to figure out what I’m most interested in.

So: on first encounter, I can appreciate some very impressive computational work going on to make this work, but it doesn’t demand that I recast my research habits to incorporate it into the normal run of things – or, at least, not yet.

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