OK here's my take on the second presentation here (responding to this mail
because it has the link to the presentation).
At first I was surprised by the huge gap between the number of founders on
enwiki (44,000) and only 2,000 on Wikidata, but then I recalled that many
COI entries on living people eventually get merged into their companies.
Though founder-company relationships are interesting, I prefer looking at
the work on the family relationships, which is something I have worked on
quite a bit for 17th-century biographies. It's a real pain to update these
in Wikidata and so it would be great to get the edits these guys prepared
loaded into some Wikigame. I also really liked their "factor graph model"
and we could use something like this as a set up for Wikigames involving
not just family relationships, but also employer-employee, prize
lists-prize recipient, alumni lists, lists of mayors, abbots and pretty
much anything that could add quality info to person items. I think it would
be really useful to followup this work with looking into ways to get their
prepared edits actually into Wikidata (with the Wikipedia reference
statements) but also ways to expand their model.
One problem we have with Wikidata are inverse properties, so e.g. famous
victims and their killers. We have a killed property but no killed by
property and so on. It would be nice to implement an easy factor graph
model for such properties so that inverse properties become unecessary.
On Wed, Jul 29, 2015 at 8:07 PM, Leila Zia <leila(a)wikimedia.org> wrote:
A friendly reminder that this is happening in 23 min.
:-)
YouTube stream:
https://www.youtube.com/watch?v=vGyrVg_qKSM
IRC: #wikimedia-research
Best,
Leila
On Mon, Jul 27, 2015 at 2:47 PM, Leila Zia <leila(a)wikimedia.org> wrote:
Hi everyone,
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!
Leila
This month:
*VisualEditor's effect on newly registered users*By *Aaron Halfaker*
<https://www.mediawiki.org/wiki/User:Halfak_%28WMF%29>
It's been nearly two years since we ran an initial study
<https://meta.wikimedia.org/wiki/Research:VisualEditor%27s_effect_on_newly_registered_editors/June_2013_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 recall analysis.
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