You could use one of the two options for reporting effect size that are
mentioned in the
Wikipedia article on the Mann Whitney Test
I recently found this test (as implemented in Python's scipy library, under
the name ranksum) useful for sorting keywords from a pair of corpora.
I got the idea from the much-missed Adam Kilgarriff's article on comparing
On 14 October 2016 at 02:52, Eric Atwell <e.s.atw...@leeds.ac.uk> wrote:
> Is there a standard metric of overlap between two ranked lists?
> e.g. to measure/score the similarity between top 10 keywords extracted
> using 2 different formulae, such as LL v MI?
> OR e.g. to measure/score the similarity between top 10 hits from Google v
> top 10 hits from Bing for a give search phrase?
> OR e.g. to measure/score the similarity between ranked lists of PoS-tags
> predicted for a word by two rival PoS-taggers in an ensemble tagger?
> If these were unranked sets of keywords, i could simply count the
> intersection. But I want to take rank into account in some senible way.
> thanks for expert pointers to proven metrics ...
> Eric Atwell, Asst Prof, Language@Leeds and Artificial Intelligence groups,
> School of Computing, University of Leeds, Times University of the Year 2017
> UNSUBSCRIBE from this page: http://mailman.uib.no/options/corpora
> Corpora mailing list
Chris Brew, Computational Scientist, Digital Operatives LLC
UNSUBSCRIBE from this page: http://mailman.uib.no/options/corpora
Corpora mailing list