(cross-posting to the research and analytics mailing lists)
Hey folks,
I've been working with a few different groups of professors, grad students
and Wikipedians to apply for grants to develop some intelligent data
services on top of the WMF labs architecture. I'm posting to ask you to
take some time to review the proposals and leave comments or an endorsement
as you see fit. I encourage you to raise conversations about each proposal
on the respective talk pages as this helps the IEG grant committee make
decisions.
https://meta.wikimedia.org/wiki/Grants:IEG/Revision_scoring_as_a_service
This is a project I have been trying to sell for a while. Counter-vandalism
tools all use their own strategy for detecting low quality edits. Some of
them use simple rule based scoring systems. Others are based on relatively
advanced machine learning strategies. The goal of this project is to solve
the revision scoring problem with advanced machine learning techniques and
to make that solution available for tool builders via a web API.
https://meta.wikimedia.org/wiki/Grants:IEG/WikiBrainTools
Brent & Shilad are professors @ UMN & Macalester College. They have been
working to develop a tool that collects information retrieval strategies
from the academic literature to make them easy to use for researchers and
wiki tool developers. This IEG is geared towards developing a web API on
top of the system to make it even easier for wiki tool developers to use.
https://meta.wikimedia.org/wiki/Grants:IEG/Automated_Notability_Detection
Per my work on Articles for Creation, it seems that a main stumbling block
for newcomer page creators and reviewers is the notability of topics. In
this project, we propose to build a machine classifier to aid in decision
making around notability. One of the core use-cases is to flag article
drafts that are clearly notable to the machine, but would otherwise be
overlooked by their human reviewers.
https://meta.wikimedia.org/wiki/Grants:IEG/Editor_Interaction_Data_Extracti…
In this project, we propose to extract varied datasets of different types
of editor interactions. Some examples include reverts, talk page reply,
user talk page, etc. We'd then use some natural language processing
strategies to identify the nature of interactions (e.g. positive vs.
negative affect). These datasets would be published openly for others to
make use of. We'd also use the data to explore hypotheses around which
types of interactions promote retention and which types of
editors/interactions lead to others leaving Wikipedia.
-Aaron
I had written about this last month. I take it there is no chance of getting the country names? As things stand the SquidReportCountryByBrowser reports are useless starting from October 2013 since the country names are not indicated!
Minutes and slides from last week's quarterly review meeting of the
Foundation's Analytics team are now available at
https://meta.wikimedia.org/wiki/WMF_Metrics_and_activities_meetings/Quarter…
.
On Wed, Dec 19, 2012 at 6:49 PM, Erik Moeller <erik(a)wikimedia.org> wrote:
> Hi folks,
>
> to increase accountability and create more opportunities for course
> corrections and resourcing adjustments as necessary, Sue's asked me
> and Howie Fung to set up a quarterly project evaluation process,
> starting with our highest priority initiatives. These are, according
> to Sue's narrowing focus recommendations which were approved by the
> Board [1]:
>
> - Visual Editor
> - Mobile (mobile contributions + Wikipedia Zero)
> - Editor Engagement (also known as the E2 and E3 teams)
> - Funds Dissemination Committe and expanded grant-making capacity
>
> I'm proposing the following initial schedule:
>
> January:
> - Editor Engagement Experiments
>
> February:
> - Visual Editor
> - Mobile (Contribs + Zero)
>
> March:
> - Editor Engagement Features (Echo, Flow projects)
> - Funds Dissemination Committee
>
> We’ll try doing this on the same day or adjacent to the monthly
> metrics meetings [2], since the team(s) will give a presentation on
> their recent progress, which will help set some context that would
> otherwise need to be covered in the quarterly review itself. This will
> also create open opportunities for feedback and questions.
>
> My goal is to do this in a manner where even though the quarterly
> review meetings themselves are internal, the outcomes are captured as
> meeting minutes and shared publicly, which is why I'm starting this
> discussion on a public list as well. I've created a wiki page here
> which we can use to discuss the concept further:
>
> https://meta.wikimedia.org/wiki/Metrics_and_activities_meetings/Quarterly_r…
>
> The internal review will, at minimum, include:
>
> Sue Gardner
> myself
> Howie Fung
> Team members and relevant director(s)
> Designated minute-taker
>
> So for example, for Visual Editor, the review team would be the Visual
> Editor / Parsoid teams, Sue, me, Howie, Terry, and a minute-taker.
>
> I imagine the structure of the review roughly as follows, with a
> duration of about 2 1/2 hours divided into 25-30 minute blocks:
>
> - Brief team intro and recap of team's activities through the quarter,
> compared with goals
> - Drill into goals and targets: Did we achieve what we said we would?
> - Review of challenges, blockers and successes
> - Discussion of proposed changes (e.g. resourcing, targets) and other
> action items
> - Buffer time, debriefing
>
> Once again, the primary purpose of these reviews is to create improved
> structures for internal accountability, escalation points in cases
> where serious changes are necessary, and transparency to the world.
>
> In addition to these priority initiatives, my recommendation would be
> to conduct quarterly reviews for any activity that requires more than
> a set amount of resources (people/dollars). These additional reviews
> may however be conducted in a more lightweight manner and internally
> to the departments. We’re slowly getting into that habit in
> engineering.
>
> As we pilot this process, the format of the high priority reviews can
> help inform and support reviews across the organization.
>
> Feedback and questions are appreciated.
>
> All best,
> Erik
>
> [1] https://wikimediafoundation.org/wiki/Vote:Narrowing_Focus
> [2] https://meta.wikimedia.org/wiki/Metrics_and_activities_meetings
> --
> Erik Möller
> VP of Engineering and Product Development, Wikimedia Foundation
>
> Support Free Knowledge: https://wikimediafoundation.org/wiki/Donate
>
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Tilman Bayer
Senior Operations Analyst (Movement Communications)
Wikimedia Foundation
IRC (Freenode): HaeB