I happen to work on a tool (initially for Liam Wyatt) that might do some of
what you want on Wikidata. Given a Wikidata Query (separate topic ;-) or a
simple list of Wikidata items, it can record changes made to these items
over time. It records the JSON for the Wikidata items, max of one
A front-end (to be written) can then extract things like number of
sitelinks (Wikipedia articles) for these items over time; Wikidata labels
in different languages; number/type of statements added; etc. Ideally, this
can be exported as a table, to make pretty stats in R (or the like).
As I said, it's work in progress, but if you have a (initial) list of
items, I can start "recording".
On Tue, Oct 6, 2015 at 4:54 PM Andrew Gray <andrew.gray(a)dunelm.org.uk>
On 6 October 2015 at 14:12, Amir E. Aharoni
Thanks for this email.
This raises a wider question: What is the comfortable way to compare the
coverage of a topic in different languages?
For example, I'd love to see a report that says:
Number of articles about UNESCO cultural heritage:
English Wikipedia: 1000
French Wikipedia: 1200
Hebrew Wikipedia: 742
And also to track this over time, so if somebody would work hard on
articles about UNESCO cultural heritage in
Hebrew, I'd see a trend graph.
There's two general approaches to this:
a) On Wikidata
b) On the individual wikis
Approach (a) would rely on having a defined set of things in Wikidata
that we can identify. For example, "is a World Heritage Site" would be
easy enough, since we have a property explicitly dealing with WHS
identifiers (and we have 100% coverage in Wikidata). "Is of interest
to UNESCO" is a trickier one - but if you can construct a suitable
As Federico notes, for WHS records, we can generate a report like
(57.4% coverage on hewiki!). No graphs but if you were interested then
you could probably set one up without much work.
b) is more useful for fuzzy groups like "of relevance to UNESCO",
since this is more or less perfect for a category system. However, it
would require examining the category tree for each WP you're
interested in to figure out exactly which categories are relevant, and
then running a script to count those daily.
- Andrew Gray
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