On Wed, Mar 16, 2016 at 7:53 PM, SarahSV <sarahsv.w...@gmail.com> wrote:

> Dario and Aaron, thanks for letting us know about this. Is the research
> available in writing for people who don't want to sit through the video?
>
> Sarah
>

Sarah – yes, see http://cm.cecs.anu.edu.au/post/wikiprivacy/

On Wed, Mar 16, 2016 at 12:55 PM, Aaron Halfaker <ahalfa...@wikimedia.org>
> wrote:
>
> > Reminder, this showcase is starting in 5 minutes.  See the stream here:
> > https://www.youtube.com/watch?v=Xle0oOFCNnk
> >
> > Join us on Freenode at #wikimedia-research
> > <http://webchat.freenode.net/?channels=wikimedia-research> to ask Andrei
> > questions.
> >
> > -Aaron
> >
> > On Tue, Mar 15, 2016 at 12:53 PM, Dario Taraborelli <
> > dtarabore...@wikimedia.org> wrote:
> >
> > > This month, our research showcase
> > > <https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase#March_2016
> >
> > hosts
> > > Andrei Rizoiu (Australian National University) to talk about his work
> > > <http://cm.cecs.anu.edu.au/post/wikiprivacy/> on *how private traits
> of
> > > Wikipedia editors can be exposed from public data* (such as edit
> > > histories) using off-the-shelf machine learning techniques. (abstract
> > below)
> > >
> > > If you're interested in learning what the combination of machine
> learning
> > > and public data mean for privacy and surveillance, come and join us
> this
> > *Wednesday
> > > March 16* at *1pm Pacific Time*.
> > >
> > > The event will be recorded and publicly streamed
> > > <https://www.youtube.com/watch?v=Xle0oOFCNnk>. As usual, we will be
> > > hosting the conversation with the speaker and Q&A on the
> > > #wikimedia-research channel on IRC.
> > >
> > > Looking forward to seeing you there,
> > >
> > > Dario
> > >
> > >
> > > Evolution of Privacy Loss in WikipediaThe cumulative effect of
> collective
> > > online participation has an important and adverse impact on individual
> > > privacy. As an online system evolves over time, new digital traces of
> > > individual behavior may uncover previously hidden statistical links
> > between
> > > an individual’s past actions and her private traits. To quantify this
> > > effect, we analyze the evolution of individual privacy loss by studying
> > > the edit history of Wikipedia over 13 years, including more than
> 117,523
> > > different users performing 188,805,088 edits. We trace each Wikipedia’s
> > > contributor using apparently harmless features, such as the number of
> > edits
> > > performed on predefined broad categories in a given time period (e.g.
> > > Mathematics, Culture or Nature). We show that even at this unspecific
> > level
> > > of behavior description, it is possible to use off-the-shelf machine
> > > learning algorithms to uncover usually undisclosed personal traits,
> such
> > as
> > > gender, religion or education. We provide empirical evidence that the
> > > prediction accuracy for almost all private traits consistently improves
> > > over time. Surprisingly, the prediction performance for users who
> stopped
> > > editing after a given time still improves. The activities performed by
> > new
> > > users seem to have contributed more to this effect than additional
> > > activities from existing (but still active) users. Insights from this
> > work
> > > should help users, system designers, and policy makers understand and
> > make
> > > long-term design choices in online content creation systems.
> > >
> > >
> > > *Dario Taraborelli  *Head of Research, Wikimedia Foundation
> > > wikimediafoundation.org • nitens.org • @readermeter
> > > <http://twitter.com/readermeter>
> > >
> > > _______________________________________________
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> > >
> > >
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-- 


*Dario Taraborelli  *Head of Research, Wikimedia Foundation
wikimediafoundation.org • nitens.org • @readermeter
<http://twitter.com/readermeter>
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