I haven’t yet had the opportunity to watch the YouTube version of the talk, but just
taking the question at face value.
I don’t think the data is likely to be able to distinguish people doing their first edits
at a training class or edit-a-thon because in general there is nothing to distinguish
these folk from any other new contributors. It might be that some events use some system
of categories for either the users or the articles (editathons often tag the articles with
the event name) so you might be able to spot edits arising from a specific event but in
general I don’t think you can tell them apart.
I teach a lot of edit training and, although I have yet to switch to the VE, I am looking
forward to being able to do so as soon as possible. Markup is definitely a barrier to some
people and I think the VE will be preferred by most users. However, while VE may make
editing easier, it does not solve the problem of having newcomers’ good faith
contributions being reverted by others. WP:NOBITE is the most ignored policy of Wikipedia.
[mailto:email@example.com] On Behalf Of Pine W
Sent: Sunday, 2 August 2015 3:58 PM
To: Wiki Research-l <wiki-research-l(a)lists.wikimedia.org>
Subject: Re: [Wiki-research-l] July 2015 Research showcase
I read the summary of the VE study, and I have a question. Anecdotally, I am hearing from
multiple sources that new editors *who attend workshops or editathons in person* prefer VE
over wikitext for ease of use. Do we have any data specifically about the productivity and
longevity of this population of users when they are introduced to to Wikipedia editing on
VE instead of wikitext?
On Jul 29, 2015 11:09 AM, "Leila Zia" <leila(a)wikimedia.org
<mailto:firstname.lastname@example.org> > wrote:
A friendly reminder that this is happening in 23 min. :-)
YouTube stream: https://www.youtube.com/watch?v=vGyrVg_qKSM
On Mon, Jul 27, 2015 at 2:47 PM, Leila Zia <leila(a)wikimedia.org
<mailto:email@example.com> > wrote:
The next Research showcase will be live-streamed this Wednesday, July 29 at 11.30 PT. The
streaming link will be posted on the lists a few minutes before the showcase starts
(sorry, we haven't been able to solve this, yet. :-() and as usual, you can join the
conversation on IRC at #wikimedia-research.
We look forward to seeing you!
VisualEditor's effect on newly registered users
By <https://www.mediawiki.org/wiki/User:Halfak_%28WMF%29> Aaron Halfaker
It's been nearly two years since we ran an initial study
of VisualEditor's effect on newly registered editors. While most of the results of
this study were positive (e.g. workload on Wikipedians did not increase), we still saw a
significant decrease in the newcomer productivity. In the meantime, the Editing
<https://www.mediawiki.org/wiki/Editing> team has made substantial improvements to
performance and functionality. In this presentation, I'll report on the results of a
new experiment designed to test the effects of enabling this improved VisualEditor
software for newly registered users by default. I'll show what we learned from the
experiment and discuss some results have opened larger questions about what, exactly, is
difficult about being a newcomer to English Wikipedia.
Wikipedia knowledge graph with DeepDive
By Juhana Kangaspunta and Thomas Palomares (10-week student project)
Despite the tremendous amount of information present on Wikipedia, only a very little
amount is structured. Most of the information is embedded in text and extracting it is a
non-trivial challenge. In this project, we try to populate Wikidata, a structured
component of Wikipedia, using DeepDive tool to extract relations embedded in the text. We
finally extracted more than 140,000 relations with more than 90% average precision. We
will present DeepDive and the data that we use for this project, we explain the relations
we focused on so far and explain the implementation and pipeline, including our model,
features and extractors. Finally, we detail our results with a thorough precision and
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