On Sun, Apr 16, 2017 at 11:58 PM, John Erling Blad <jeblad(a)gmail.com> wrote:
Definitly part of the overall quality. I wonder, do
you have any stats om
how much positive change the previous attempts have triggered?
[John and I went off-list for me to understand which specific previous
attempts he had in mind when asking the above. I have a better sense now
and I'm responding to that.]
I'm providing some pointers to indications or controlled experiment results
that show how well recommendations in the space of article creation work
(Note that I don't have results for the article expansion work to share for
now.):
We built an end-to-end system that identifies missing articles in a given
language, ranks them according to their importance in that given language,
and recommends them to editors who are interested to create them (interest
is inferred based on the topic of the articles the editor has edited in the
recent past). We ran a controlled experiment and showed that you can
increase article creation rate in Wikipedia by a factor of 3.2 if you do
personalized recommendations in the setting of the experiment (which was
editors receiving recommendations over email) while maintaining the same
level of quality as organically created articles on Wikipedia. We also
showed that personalized recommendations increase article creation rate by
a factor of almost 2 when compared to non-personalized recommendations. If
you are interested about the details of this study, you can read the paper
that describes it fully at
https://arxiv.org/abs/1604.03235. If you prefer
a verbal presentation on this topic, I've recently presented this work, why
it's important, and some of the work we've started in the article expansion
research in CITRIS Exchange seminar series
<http://citris-uc.org/spring-2017-citris-research-exchange-seminar-series/> in
University of California, Berkeley. You can check out the presentation
slides
<https://commons.wikimedia.org/wiki/File:Growing_Wikipedia_Across_Languages_via_Recommendations_CITRIS_20170315.pdf>
and the video of the presentation
<https://www.youtube.com/watch?v=lHbnvRwFC_A&index=7&list=PLYTiwx6hV33vqwW7HWyYHMca4H0Ru6KQT>
.
Outside of the experimental setting, Content Translation is using the
recommendation
API <https://meta.wikimedia.org/wiki/Recommendation_API> behind the
research I explained above as part of their "Suggestions" feature. Every
week, around 180 articles get published on Wikipedia using Suggestions
feature alone. This is around 6-9% of all articles created via Content
Translation every week. So, we have some evidence that in practice, these
recommendations work, too.
I hope this helps.
Best,
Leila
Den man. 17. apr. 2017, 02.04 skrev Leila Zia <leila(a)wikimedia.org>rg>:
Hi John,
This may be of interest to you:
We are working on building recommendation systems than can help editors
identify how to expand already existing articles in Wikipedia. This
includes but is not limited to identifying what sections are missing from
an article, what citations, what images, infobox information, etc. This
is
research in its early days, if you'd like to
follow up with it please
visit
_stubs_across_languages
Best,
Leila
Leila Zia
Senior Research Scientist
Wikimedia Foundation
On Sat, Apr 15, 2017 at 2:50 PM, John Erling Blad <jeblad(a)gmail.com>
wrote:
> Are anyone doing any work on automated quality assurance of articles?
Not
> the ORES-stuff, that is about creating hints
from measured features.
I'm
thinking
about verifying existence and completeness of citations, and
structure of logical arguments.
John
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