Hi everyone,
The next Research Showcase will be live-streamed on Wednesday, March 20, at
9:30 AM PST / 16:30 UTC. Find your local time here
<https://zonestamp.toolforge.org/1710952200>. In line with Women's History
Month, the theme for this showcase is *Addressing Knowledge Gaps*.
You are welcome to watch via the YouTube stream:
https://www.youtube.com/watch?v=D6wrr9WShTk. As usual, you can join the
conversation in the YouTube chat as soon as the showcase goes live.
This month's presentation:
Leveraging Recommender Systems to Reduce Content Gaps on WikipediaBy *Mo
Houtti*Many Wikipedians use algorithmic recommender systems to help them
find interesting articles to edit. The algorithms underlying those systems
are driven by a straightforward assumption: we can look at what someone
edited in the past to figure out what they’ll most likely want to edit
next. But the story of what Wikipedians want to edit is almost definitely
more complex than that. For example, our own prior research shows that
Wikipedians prefer prioritizing articles that would minimize content gaps.
So, we asked, what would happen if we incorporated that value into
Wikipedians’ personalized recommendations? Through a controlled experiment
on SuggestBot, we found that recommending more content gap articles didn’t
significantly impact editing, despite those articles being less “optimally
interesting” according to the recommendation algorithm. In this
presentation, I will describe our experiment, our results, and their
implications - including how recommender systems can be one useful strategy
for tackling content gaps on Wikipedia.Bridging the offline and online-
Offline meetings of WikipediansBy *Nicole Schwitter*Wikipedia is primarily
known as an online encyclopaedia, but it also features a noteworthy offline
component: Wikipedia and particularly its German-language edition – which
is one of the largest and most active language versions – is characterised
by regular local offline meetups which give editors the chance to get to
know each other. This talk will present the recently published dewiki
meetup dataset which covers (almost) all offline gatherings organised on
the German-language version of Wikipedia. The dataset covers almost 20
years of offline activity of the German-language Wikipedia, containing 4418
meetups that have been organised with information on attendees, apologies,
date and place of meeting, and minutes recorded. The talk will explain how
the dataset can be used for research, highlight the importance of
considering offline meetings among Wikipedians, and place these insights
within the context of addressing gender gaps within Wikipedia.
Best,
Kinneret
--
Kinneret Gordon
Lead Research Community Officer
Wikimedia Foundation <https://wikimediafoundation.org/>
Hello (especially to Superset users),
As you may know, the Data Platform SRE team is currently working on
migrating the Analytics Superset instances to Kubernetes (under ticket
T347710 <https://phabricator.wikimedia.org/T347710>) and, happily, I can
report that we are making good progress.
This is just a courtesy email to let you know that we plan to switch our
staging instance (superset-next.wikimedia.org
<https://superset-next.wikimedia.org>) to over to Kubernetes over the
next day or two. This is unlikely to affect anyone's work at the moment,
given that both the staging and production instances of Superset have
been on version 3.1.0 for a while.
However, given that this staging instance is available for you to use at
any time, we thought it best to let you know that we are currently
working on it and that it may be in a state of flux for a while.
Once it is stable on Kubernetes, we may well contact you again and ask
you kindly to test superset-next for us and report your findings. At the
moment though, we're just working on the transition itself so there
won't be much for you to test.
As ever, if you have any queries or concerns, please don't hesitate to
let us know.
Kind regards,
Ben
--
*Ben Tullis*(he/him)
Senior Site Reliability Engineer
Wikimedia Foundation <https://wikimediafoundation.org/>
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Hello,
If you don't use the GPUs on the stat servers you can skip the rest of
this message.
If you do use stat1005 and its GPU, please be aware that we are planning
to move this GPU to a new stat server stat1010 as soon as it's feasible
to do so. Hopefully within a week or two.
Please could you let us know if this would be inconvenient for you and
we will try to accommodate your needs. We'll let you know a precise date
for the GPU move once we have assessed the current usage and have
planned the work with the DC Ops team in eqiad.
If you still need to use a GPU on buster, you can continue to use
stat1008 for now.
As ever, if you have any queries or concerns about these operations,
please do let us know.
Kind regards,
Ben
--
*Ben Tullis*(he/him)
Senior Site Reliability Engineer
Wikimedia Foundation <https://wikimediafoundation.org/>