*tl;dr: We'll be stripping all content contained inside brackets from the
first sentence of articles in the Wikipedia app.*
The Mobile Apps Team is focussed on making the app a beautiful and engaging
reader experience, and trying to support use cases like wanting to look
something up quickly to find what it is. Unfortunately, there are several
aspects of Wikipedia at present that are actively detrimental to that goal.
One example of this are the lead sentences.
As mentioned in the other thread on this matter
lead sentences are poorly formatted and contain information that is
detrimental to quickly looking up a topic. The team did a quick audit
the information available inside brackets in the first sentences, and
typically it is pronunciation information which is probably better placed
in the infobox rather than breaking up the first sentence. The other
problem is that this information was typically inserted and previewed on a
platform where space is not at a premium, and that calculation is different
on mobile devices.
In order to better serve the quick lookup use case, the team has reached
the decision to strip anything inside brackets in the first sentence of
articles in the Wikipedia app.
Stripping content is not a decision to be made lightly. People took the
time to write it, and that should be respected. We realise this is
controversial. That said, it's the opinion of the team that the problem is
pretty clear: this content is not optimised for users quickly looking
things up on mobile devices at all, and will take a long time to solve
through alternative means. A quicker solution is required.
The screenshots below are mockups of the before and after of the change.
These are not final, I just put them together quickly to illustrate what
I'm talking about.
- Before: http://i.imgur.com/VwKerbv.jpg
- After: http://i.imgur.com/2A5PLmy.jpg
If you have any questions, let me know.
Associate Product Manager, Mobile Apps
As mentioned previously, the current version of the Android app contains an
A/B test where it presents "read more" suggestions to the user, based on
(a) the standard "morelike" query, or (b) the new "opening_text" query.
Here are the results from the last ~10 days of the test:
- The clickthrough rate using the default morelike query is (and has been)
- With the new opening_text query, the clickthrough rate decreases to about
[image: Inline image 1]
Therefore, it seems that the new query has a nontrivial negative effect on
We'll plan on removing this test in the next release of the app, but we'll
be happy to plug in a different or updated query, if it will be of further
use to Discovery.
(queries embedded as comments in the headers)
Senior Software Engineer / Product Owner (Android)
(Another) cross post.
As a reminder the CREDIT Showcase is next week on Wednesday,
1-February-2017 (see https://www.mediawiki.org/wiki/CREDIT_showcase for
details). Also, as I mentioned previously we're conducting a survey about
CREDIT. We'd appreciate your feedback! Here is a link to the survey (which
is hosted on a third-party service), and, for information about privacy and
data handling, the survey privacy statement.
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And, as usual, if you'd like to share the news about the upcoming CREDIT,
here's some suggested verbiage.
*I hope all is well with you! I wanted to let you know about CREDIT, a
monthly demo series that we’re running to showcase open source tech
projects from Wikimedia’s Community, Reading, Editing, Discovery,
Infrastructure and Technology teams. *
*CREDIT is open to the public, and we welcome questions and discussion. The
next CREDIT will be held on February 1st at 11am PT / 2pm ET / 19:00 UTC. *
*There’s more info on MediaWiki
<https://www.mediawiki.org/wiki/CREDIT_showcase>, and on Etherpad
<https://etherpad.wikimedia.org/p/CREDIT>, which is where we take notes and
ask questions. You can also ask questions on IRC in the Freenode chatroom
#wikimedia-office (web-based access here
<https://webchat.freenode.net/?channels=%23wikimedia-office>). Links to
video will become available at these locations shortly before the event.*
*Please feel free to pass this information along to any interested folks.
Our projects tend to focus on areas that might be of interest to folks
working across the open source tech community: language detection,
numerical sort, large data visualizations, maps, and all sorts of other
*If you have any questions, please let me know! Thanks, and I hope to see
you at CREDIT.*
Director of Engineering, Reading
Is it considered acceptable now to produce a service or API that
hardcodes wiki-specific parsing of certain wikitext or HTML patterns in
certain wiki pages (such as the "On this day" section of the main page
of one wiki)?
I'm confused by the status of things and after my comment
https://phabricator.wikimedia.org/T143408#2919000 I see little effort on
finding solutions potentially able to scale to all our projects and
languages (which I assume to be the mission, see "globally" in
https://wikimediafoundation.org/wiki/Mission_statement ; please point it
out if this assumption is incorrect).
It might be that wiki-specific parsing hardcoded in MediaWiki/Wikimedia
code is actually able to scale, if written correctly; a comment on the
association patch seemed to imply so. This would be a very surprising
finding, and one which goes against 15 years of experience, so if we
have some examples or evidence of this it would be very worthwhile to
point them out.
Live from the Dev Summit, we just released a small update for the
Wikipedia iOS app to the App Store. Version 5.3.4 includes a handful
of stability and bug fixes, particularly when starting the app or
using the Share-a-fact feature.
PM, Wikipedia for iOS
Happy new year! New year, new version...
We just posted a first beta of v5.3.4 to our TestFlight beta channel. This
version improves stability, particularly at start up and with image
loading, along with a handful of other bug fixes.
If you'd like to sign up as a beta tester, please join us here:
PM, Wikipedia for iOS