[Wikimedia Research Showcase] June 26, 2019 at 11:30 AM PST, 19:30 UTC

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[Wikimedia Research Showcase] June 26, 2019 at 11:30 AM PST, 19:30 UTC

Janna Layton
Hi all,

The next Research Showcase will be live-streamed this Wednesday, June 26,
at 11:30 AM PST/19:30 UTC. We will have three presentations this showcase,
all relating to Wikipedia blocks.

YouTube stream: https://www.youtube.com/watch?v=WiUfpmeJG7E

As usual, you can join the conversation on IRC at #wikimedia-research. You
can also watch our past research showcases here:
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase

This month's presentations:

Trajectories of Blocked Community Members: Redemption, Recidivism and
Departure

By Jonathan Chang, Cornell University

Community norm violations can impair constructive communication and
collaboration online. As a defense mechanism, community moderators often
address such transgressions by temporarily blocking the perpetrator. Such
actions, however, come with the cost of potentially alienating community
members. Given this tradeoff, it is essential to understand to what extent,
and in which situations, this common moderation practice is effective in
reinforcing community rules. In this work, we introduce a computational
framework for studying the future behavior of blocked users on Wikipedia.
After their block expires, they can take several distinct paths: they can
reform and adhere to the rules, but they can also recidivate, or
straight-out abandon the community. We reveal that these trajectories are
tied to factors rooted both in the characteristics of the blocked
individual and in whether they perceived the block to be fair and
justified. Based on these insights, we formulate a series of prediction
tasks aiming to determine which of these paths a user is likely to take
after being blocked for their first offense, and demonstrate the
feasibility of these new tasks. Overall, this work builds towards a more
nuanced approach to moderation by highlighting the tradeoffs that are in
play.


Automatic Detection of Online Abuse in Wikipedia

By Lane Rasberry, University of Virginia

Researchers analyzed all English Wikipedia blocks prior to 2018 using
machine learning. With insights gained, the researchers examined all
English Wikipedia users who are not blocked against the identified
characteristics of blocked users. The results were a ranked set of
predictions of users who are not blocked, but who have a history of conduct
similar to that of blocked users. This research and process models a system
for the use of computing to aid human moderators in identifying conduct on
English Wikipedia which merits a block.

Project page:
https://meta.wikimedia.org/wiki/University_of_Virginia/Automatic_Detection_of_Online_Abuse

Video: https://www.youtube.com/watch?v=AIhdb4-hKBo


First Insights from Partial Blocks in Wikimedia Wikis

By Morten Warncke-Wang, Wikimedia Foundation

The Anti-Harassment Tools team at the Wikimedia Foundation released the
partial block feature in early 2019. Where previously blocks on Wikimedia
wikis were sitewide (users were blocked from editing an entire wiki),
partial blocks makes it possible to block users from editing specific pages
and/or namespaces. The Italian Wikipedia was the first wiki to start using
this feature, and it has since been rolled out to other wikis as well. In
this presentation, we will look at how this feature has been used in the
first few months since release.


--
Janna Layton (she, her)
Administrative Assistant - Audiences & Technology
Wikimedia Foundation <https://wikimediafoundation.org/>
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Re: [Wikimedia Research Showcase] June 26, 2019 at 11:30 AM PST, 19:30 UTC

Janna Layton
Hello everyone,

Just a reminder that this event will be happening in about half an hour!
Here's the Youtube link again: https://www.youtube.com/watch?v=WiUfpmeJG7E

On Tue, Jun 25, 2019 at 9:14 AM Janna Layton <[hidden email]> wrote:

> Time correction:
>
> The next Research Showcase will be live-streamed next Wednesday, June 26,
> at *11:30 AM PDT/18:30 UTC*.
>
> On Mon, Jun 24, 2019 at 4:11 PM Janna Layton <[hidden email]>
> wrote:
>
>> Hi all,
>>
>> The next Research Showcase will be live-streamed this Wednesday, June 26,
>> at 11:30 AM PST/19:30 UTC. We will have three presentations this showcase,
>> all relating to Wikipedia blocks.
>>
>> YouTube stream: https://www.youtube.com/watch?v=WiUfpmeJG7E
>>
>> As usual, you can join the conversation on IRC at #wikimedia-research.
>> You can also watch our past research showcases here:
>> https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
>>
>> This month's presentations:
>>
>> Trajectories of Blocked Community Members: Redemption, Recidivism and
>> Departure
>>
>> By Jonathan Chang, Cornell University
>>
>> Community norm violations can impair constructive communication and
>> collaboration online. As a defense mechanism, community moderators often
>> address such transgressions by temporarily blocking the perpetrator. Such
>> actions, however, come with the cost of potentially alienating community
>> members. Given this tradeoff, it is essential to understand to what extent,
>> and in which situations, this common moderation practice is effective in
>> reinforcing community rules. In this work, we introduce a computational
>> framework for studying the future behavior of blocked users on Wikipedia.
>> After their block expires, they can take several distinct paths: they can
>> reform and adhere to the rules, but they can also recidivate, or
>> straight-out abandon the community. We reveal that these trajectories are
>> tied to factors rooted both in the characteristics of the blocked
>> individual and in whether they perceived the block to be fair and
>> justified. Based on these insights, we formulate a series of prediction
>> tasks aiming to determine which of these paths a user is likely to take
>> after being blocked for their first offense, and demonstrate the
>> feasibility of these new tasks. Overall, this work builds towards a more
>> nuanced approach to moderation by highlighting the tradeoffs that are in
>> play.
>>
>>
>> Automatic Detection of Online Abuse in Wikipedia
>>
>> By Lane Rasberry, University of Virginia
>>
>> Researchers analyzed all English Wikipedia blocks prior to 2018 using
>> machine learning. With insights gained, the researchers examined all
>> English Wikipedia users who are not blocked against the identified
>> characteristics of blocked users. The results were a ranked set of
>> predictions of users who are not blocked, but who have a history of conduct
>> similar to that of blocked users. This research and process models a system
>> for the use of computing to aid human moderators in identifying conduct on
>> English Wikipedia which merits a block.
>>
>> Project page:
>> https://meta.wikimedia.org/wiki/University_of_Virginia/Automatic_Detection_of_Online_Abuse
>>
>> Video: https://www.youtube.com/watch?v=AIhdb4-hKBo
>>
>>
>> First Insights from Partial Blocks in Wikimedia Wikis
>>
>> By Morten Warncke-Wang, Wikimedia Foundation
>>
>> The Anti-Harassment Tools team at the Wikimedia Foundation released the
>> partial block feature in early 2019. Where previously blocks on Wikimedia
>> wikis were sitewide (users were blocked from editing an entire wiki),
>> partial blocks makes it possible to block users from editing specific pages
>> and/or namespaces. The Italian Wikipedia was the first wiki to start using
>> this feature, and it has since been rolled out to other wikis as well. In
>> this presentation, we will look at how this feature has been used in the
>> first few months since release.
>>
>>
>> --
>> Janna Layton (she, her)
>> Administrative Assistant - Audiences & Technology
>> Wikimedia Foundation <https://wikimediafoundation.org/>
>>
>
>
> --
> Janna Layton (she, her)
> Administrative Assistant - Audiences & Technology
> Wikimedia Foundation <https://wikimediafoundation.org/>
>


--
Janna Layton (she, her)
Administrative Assistant - Audiences & Technology
Wikimedia Foundation <https://wikimediafoundation.org/>
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Re: [Analytics] [Wikimedia Research Showcase] June 26, 2019 at 11:30 AM PST, 19:30 UTC

RhinosF1 Wikipedia
For those that couldn't make it, Is there are summary of what was said?

Thanks in advance,
RhinosF1

On Wed, 26 Jun 2019 at 18:58, Janna Layton <[hidden email]> wrote:

> Hello everyone,
>
> Just a reminder that this event will be happening in about half an hour!
> Here's the Youtube link again: https://www.youtube.com/watch?v=WiUfpmeJG7E
>
> On Tue, Jun 25, 2019 at 9:14 AM Janna Layton <[hidden email]>
> wrote:
>
>> Time correction:
>>
>> The next Research Showcase will be live-streamed next Wednesday, June 26,
>> at *11:30 AM PDT/18:30 UTC*.
>>
>> On Mon, Jun 24, 2019 at 4:11 PM Janna Layton <[hidden email]>
>> wrote:
>>
>>> Hi all,
>>>
>>> The next Research Showcase will be live-streamed this Wednesday, June
>>> 26, at 11:30 AM PST/19:30 UTC. We will have three presentations this
>>> showcase, all relating to Wikipedia blocks.
>>>
>>> YouTube stream: https://www.youtube.com/watch?v=WiUfpmeJG7E
>>>
>>> As usual, you can join the conversation on IRC at #wikimedia-research.
>>> You can also watch our past research showcases here:
>>> https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
>>>
>>> This month's presentations:
>>>
>>> Trajectories of Blocked Community Members: Redemption, Recidivism and
>>> Departure
>>>
>>> By Jonathan Chang, Cornell University
>>>
>>> Community norm violations can impair constructive communication and
>>> collaboration online. As a defense mechanism, community moderators often
>>> address such transgressions by temporarily blocking the perpetrator. Such
>>> actions, however, come with the cost of potentially alienating community
>>> members. Given this tradeoff, it is essential to understand to what extent,
>>> and in which situations, this common moderation practice is effective in
>>> reinforcing community rules. In this work, we introduce a computational
>>> framework for studying the future behavior of blocked users on Wikipedia.
>>> After their block expires, they can take several distinct paths: they can
>>> reform and adhere to the rules, but they can also recidivate, or
>>> straight-out abandon the community. We reveal that these trajectories are
>>> tied to factors rooted both in the characteristics of the blocked
>>> individual and in whether they perceived the block to be fair and
>>> justified. Based on these insights, we formulate a series of prediction
>>> tasks aiming to determine which of these paths a user is likely to take
>>> after being blocked for their first offense, and demonstrate the
>>> feasibility of these new tasks. Overall, this work builds towards a more
>>> nuanced approach to moderation by highlighting the tradeoffs that are in
>>> play.
>>>
>>>
>>> Automatic Detection of Online Abuse in Wikipedia
>>>
>>> By Lane Rasberry, University of Virginia
>>>
>>> Researchers analyzed all English Wikipedia blocks prior to 2018 using
>>> machine learning. With insights gained, the researchers examined all
>>> English Wikipedia users who are not blocked against the identified
>>> characteristics of blocked users. The results were a ranked set of
>>> predictions of users who are not blocked, but who have a history of conduct
>>> similar to that of blocked users. This research and process models a system
>>> for the use of computing to aid human moderators in identifying conduct on
>>> English Wikipedia which merits a block.
>>>
>>> Project page:
>>> https://meta.wikimedia.org/wiki/University_of_Virginia/Automatic_Detection_of_Online_Abuse
>>>
>>> Video: https://www.youtube.com/watch?v=AIhdb4-hKBo
>>>
>>>
>>> First Insights from Partial Blocks in Wikimedia Wikis
>>>
>>> By Morten Warncke-Wang, Wikimedia Foundation
>>>
>>> The Anti-Harassment Tools team at the Wikimedia Foundation released the
>>> partial block feature in early 2019. Where previously blocks on Wikimedia
>>> wikis were sitewide (users were blocked from editing an entire wiki),
>>> partial blocks makes it possible to block users from editing specific pages
>>> and/or namespaces. The Italian Wikipedia was the first wiki to start using
>>> this feature, and it has since been rolled out to other wikis as well. In
>>> this presentation, we will look at how this feature has been used in the
>>> first few months since release.
>>>
>>>
>>> --
>>> Janna Layton (she, her)
>>> Administrative Assistant - Audiences & Technology
>>> Wikimedia Foundation <https://wikimediafoundation.org/>
>>>
>>
>>
>> --
>> Janna Layton (she, her)
>> Administrative Assistant - Audiences & Technology
>> Wikimedia Foundation <https://wikimediafoundation.org/>
>>
>
>
> --
> Janna Layton (she, her)
> Administrative Assistant - Audiences & Technology
> Wikimedia Foundation <https://wikimediafoundation.org/>
> _______________________________________________
> Analytics mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/analytics
>
_______________________________________________
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[hidden email]
https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
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Re: [Analytics] [Wikimedia Research Showcase] June 26, 2019 at 11:30 AM PST, 19:30 UTC

James Salsman-2
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Re: [Analytics] [Wikimedia Research Showcase] June 26, 2019 at 11:30 AM PST, 19:30 UTC

Leila Zia
Hi James,

Beyond the abstract of the talk at
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase#June_2019
and section 7 of the full paper (the full paper is linked from the
abstract as well:
http://www.cs.cornell.edu/~jpchang/papers/recidivism_online.pdf ), I'm
not aware of any other summaries.

Best,
Leila
p.s. inspired by your question, I'm thinking maybe we should ask
Jonathan Chang to write a blog post about it. That's for later though.
:)

--
Leila Zia
Principal Research Scientist, Head of Research
Wikimedia Foundation

On Thu, Jun 27, 2019 at 2:50 PM James Salsman <[hidden email]> wrote:

>
> > For those that couldn't make it, Is there are summary of what was said?
>
> Full recording: https://www.youtube.com/watch?v=WiUfpmeJG7E
>
> Slides:
>
> https://www.mediawiki.org/wiki/File:Trajectories_of_Blocked_Community_Members_-_Slides.pdf
>
> https://meta.wikimedia.org/wiki/University_of_Virginia/Automatic_Detection_of_Online_Abuse
>
> _______________________________________________
> Analytics mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/analytics

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Re: [Analytics] [Wikimedia Research Showcase] June 26, 2019 at 11:30 AM PST, 19:30 UTC

Jonathan Morgan
In reply to this post by RhinosF1 Wikipedia
RhinosF1,

All talks are recorded and archived on YouTube, so the link below should
still work. Let me know if there's a problem with the archiving and I'll
see what I can do. I'm also working on getting all slides linked to from
the Showcase page on me.org, whenever possible!

It was a great series of talks this week. Hope you enjoy it! -J

On Wed, Jun 26, 2019, 19:04 RhinosF1 Wikipedia <[hidden email]> wrote:

> For those that couldn't make it, Is there are summary of what was said?
>
> Thanks in advance,
> RhinosF1
>
> On Wed, 26 Jun 2019 at 18:58, Janna Layton <[hidden email]> wrote:
>
>> Hello everyone,
>>
>> Just a reminder that this event will be happening in about half an hour!
>> Here's the Youtube link again:
>> https://www.youtube.com/watch?v=WiUfpmeJG7E
>>
>> On Tue, Jun 25, 2019 at 9:14 AM Janna Layton <[hidden email]>
>> wrote:
>>
>>> Time correction:
>>>
>>> The next Research Showcase will be live-streamed next Wednesday, June
>>> 26, at *11:30 AM PDT/18:30 UTC*.
>>>
>>> On Mon, Jun 24, 2019 at 4:11 PM Janna Layton <[hidden email]>
>>> wrote:
>>>
>>>> Hi all,
>>>>
>>>> The next Research Showcase will be live-streamed this Wednesday, June
>>>> 26, at 11:30 AM PST/19:30 UTC. We will have three presentations this
>>>> showcase, all relating to Wikipedia blocks.
>>>>
>>>> YouTube stream: https://www.youtube.com/watch?v=WiUfpmeJG7E
>>>>
>>>> As usual, you can join the conversation on IRC at #wikimedia-research.
>>>> You can also watch our past research showcases here:
>>>> https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
>>>>
>>>> This month's presentations:
>>>>
>>>> Trajectories of Blocked Community Members: Redemption, Recidivism and
>>>> Departure
>>>>
>>>> By Jonathan Chang, Cornell University
>>>>
>>>> Community norm violations can impair constructive communication and
>>>> collaboration online. As a defense mechanism, community moderators often
>>>> address such transgressions by temporarily blocking the perpetrator. Such
>>>> actions, however, come with the cost of potentially alienating community
>>>> members. Given this tradeoff, it is essential to understand to what extent,
>>>> and in which situations, this common moderation practice is effective in
>>>> reinforcing community rules. In this work, we introduce a computational
>>>> framework for studying the future behavior of blocked users on Wikipedia.
>>>> After their block expires, they can take several distinct paths: they can
>>>> reform and adhere to the rules, but they can also recidivate, or
>>>> straight-out abandon the community. We reveal that these trajectories are
>>>> tied to factors rooted both in the characteristics of the blocked
>>>> individual and in whether they perceived the block to be fair and
>>>> justified. Based on these insights, we formulate a series of prediction
>>>> tasks aiming to determine which of these paths a user is likely to take
>>>> after being blocked for their first offense, and demonstrate the
>>>> feasibility of these new tasks. Overall, this work builds towards a more
>>>> nuanced approach to moderation by highlighting the tradeoffs that are in
>>>> play.
>>>>
>>>>
>>>> Automatic Detection of Online Abuse in Wikipedia
>>>>
>>>> By Lane Rasberry, University of Virginia
>>>>
>>>> Researchers analyzed all English Wikipedia blocks prior to 2018 using
>>>> machine learning. With insights gained, the researchers examined all
>>>> English Wikipedia users who are not blocked against the identified
>>>> characteristics of blocked users. The results were a ranked set of
>>>> predictions of users who are not blocked, but who have a history of conduct
>>>> similar to that of blocked users. This research and process models a system
>>>> for the use of computing to aid human moderators in identifying conduct on
>>>> English Wikipedia which merits a block.
>>>>
>>>> Project page:
>>>> https://meta.wikimedia.org/wiki/University_of_Virginia/Automatic_Detection_of_Online_Abuse
>>>>
>>>> Video: https://www.youtube.com/watch?v=AIhdb4-hKBo
>>>>
>>>>
>>>> First Insights from Partial Blocks in Wikimedia Wikis
>>>>
>>>> By Morten Warncke-Wang, Wikimedia Foundation
>>>>
>>>> The Anti-Harassment Tools team at the Wikimedia Foundation released the
>>>> partial block feature in early 2019. Where previously blocks on Wikimedia
>>>> wikis were sitewide (users were blocked from editing an entire wiki),
>>>> partial blocks makes it possible to block users from editing specific pages
>>>> and/or namespaces. The Italian Wikipedia was the first wiki to start using
>>>> this feature, and it has since been rolled out to other wikis as well. In
>>>> this presentation, we will look at how this feature has been used in the
>>>> first few months since release.
>>>>
>>>>
>>>> --
>>>> Janna Layton (she, her)
>>>> Administrative Assistant - Audiences & Technology
>>>> Wikimedia Foundation <https://wikimediafoundation.org/>
>>>>
>>>
>>>
>>> --
>>> Janna Layton (she, her)
>>> Administrative Assistant - Audiences & Technology
>>> Wikimedia Foundation <https://wikimediafoundation.org/>
>>>
>>
>>
>> --
>> Janna Layton (she, her)
>> Administrative Assistant - Audiences & Technology
>> Wikimedia Foundation <https://wikimediafoundation.org/>
>> _______________________________________________
>> Analytics mailing list
>> [hidden email]
>> https://lists.wikimedia.org/mailman/listinfo/analytics
>>
> _______________________________________________
> Analytics mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/analytics
>
_______________________________________________
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Re: [Analytics] [Wikimedia Research Showcase] June 26, 2019 at 11:30 AM PST, 19:30 UTC

RhinosF1 Wikipedia
Thanks Jonathan

On Thu, 27 Jun 2019 at 16:07, Jonathan Morgan <[hidden email]> wrote:

> RhinosF1,
>
> All talks are recorded and archived on YouTube, so the link below should
> still work. Let me know if there's a problem with the archiving and I'll
> see what I can do. I'm also working on getting all slides linked to from
> the Showcase page on me.org, whenever possible!
>
> It was a great series of talks this week. Hope you enjoy it! -J
>
> On Wed, Jun 26, 2019, 19:04 RhinosF1 Wikipedia <[hidden email]> wrote:
>
> > For those that couldn't make it, Is there are summary of what was said?
> >
> > Thanks in advance,
> > RhinosF1
> >
> > On Wed, 26 Jun 2019 at 18:58, Janna Layton <[hidden email]>
> wrote:
> >
> >> Hello everyone,
> >>
> >> Just a reminder that this event will be happening in about half an hour!
> >> Here's the Youtube link again:
> >> https://www.youtube.com/watch?v=WiUfpmeJG7E
> >>
> >> On Tue, Jun 25, 2019 at 9:14 AM Janna Layton <[hidden email]>
> >> wrote:
> >>
> >>> Time correction:
> >>>
> >>> The next Research Showcase will be live-streamed next Wednesday, June
> >>> 26, at *11:30 AM PDT/18:30 UTC*.
> >>>
> >>> On Mon, Jun 24, 2019 at 4:11 PM Janna Layton <[hidden email]>
> >>> wrote:
> >>>
> >>>> Hi all,
> >>>>
> >>>> The next Research Showcase will be live-streamed this Wednesday, June
> >>>> 26, at 11:30 AM PST/19:30 UTC. We will have three presentations this
> >>>> showcase, all relating to Wikipedia blocks.
> >>>>
> >>>> YouTube stream: https://www.youtube.com/watch?v=WiUfpmeJG7E
> >>>>
> >>>> As usual, you can join the conversation on IRC at #wikimedia-research.
> >>>> You can also watch our past research showcases here:
> >>>> https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
> >>>>
> >>>> This month's presentations:
> >>>>
> >>>> Trajectories of Blocked Community Members: Redemption, Recidivism and
> >>>> Departure
> >>>>
> >>>> By Jonathan Chang, Cornell University
> >>>>
> >>>> Community norm violations can impair constructive communication and
> >>>> collaboration online. As a defense mechanism, community moderators
> often
> >>>> address such transgressions by temporarily blocking the perpetrator.
> Such
> >>>> actions, however, come with the cost of potentially alienating
> community
> >>>> members. Given this tradeoff, it is essential to understand to what
> extent,
> >>>> and in which situations, this common moderation practice is effective
> in
> >>>> reinforcing community rules. In this work, we introduce a
> computational
> >>>> framework for studying the future behavior of blocked users on
> Wikipedia.
> >>>> After their block expires, they can take several distinct paths: they
> can
> >>>> reform and adhere to the rules, but they can also recidivate, or
> >>>> straight-out abandon the community. We reveal that these trajectories
> are
> >>>> tied to factors rooted both in the characteristics of the blocked
> >>>> individual and in whether they perceived the block to be fair and
> >>>> justified. Based on these insights, we formulate a series of
> prediction
> >>>> tasks aiming to determine which of these paths a user is likely to
> take
> >>>> after being blocked for their first offense, and demonstrate the
> >>>> feasibility of these new tasks. Overall, this work builds towards a
> more
> >>>> nuanced approach to moderation by highlighting the tradeoffs that are
> in
> >>>> play.
> >>>>
> >>>>
> >>>> Automatic Detection of Online Abuse in Wikipedia
> >>>>
> >>>> By Lane Rasberry, University of Virginia
> >>>>
> >>>> Researchers analyzed all English Wikipedia blocks prior to 2018 using
> >>>> machine learning. With insights gained, the researchers examined all
> >>>> English Wikipedia users who are not blocked against the identified
> >>>> characteristics of blocked users. The results were a ranked set of
> >>>> predictions of users who are not blocked, but who have a history of
> conduct
> >>>> similar to that of blocked users. This research and process models a
> system
> >>>> for the use of computing to aid human moderators in identifying
> conduct on
> >>>> English Wikipedia which merits a block.
> >>>>
> >>>> Project page:
> >>>>
> https://meta.wikimedia.org/wiki/University_of_Virginia/Automatic_Detection_of_Online_Abuse
> >>>>
> >>>> Video: https://www.youtube.com/watch?v=AIhdb4-hKBo
> >>>>
> >>>>
> >>>> First Insights from Partial Blocks in Wikimedia Wikis
> >>>>
> >>>> By Morten Warncke-Wang, Wikimedia Foundation
> >>>>
> >>>> The Anti-Harassment Tools team at the Wikimedia Foundation released
> the
> >>>> partial block feature in early 2019. Where previously blocks on
> Wikimedia
> >>>> wikis were sitewide (users were blocked from editing an entire wiki),
> >>>> partial blocks makes it possible to block users from editing specific
> pages
> >>>> and/or namespaces. The Italian Wikipedia was the first wiki to start
> using
> >>>> this feature, and it has since been rolled out to other wikis as
> well. In
> >>>> this presentation, we will look at how this feature has been used in
> the
> >>>> first few months since release.
> >>>>
> >>>>
> >>>> --
> >>>> Janna Layton (she, her)
> >>>> Administrative Assistant - Audiences & Technology
> >>>> Wikimedia Foundation <https://wikimediafoundation.org/>
> >>>>
> >>>
> >>>
> >>> --
> >>> Janna Layton (she, her)
> >>> Administrative Assistant - Audiences & Technology
> >>> Wikimedia Foundation <https://wikimediafoundation.org/>
> >>>
> >>
> >>
> >> --
> >> Janna Layton (she, her)
> >> Administrative Assistant - Audiences & Technology
> >> Wikimedia Foundation <https://wikimediafoundation.org/>
> >> _______________________________________________
> >> Analytics mailing list
> >> [hidden email]
> >> https://lists.wikimedia.org/mailman/listinfo/analytics
> >>
> > _______________________________________________
> > Analytics mailing list
> > [hidden email]
> > https://lists.wikimedia.org/mailman/listinfo/analytics
> >
> _______________________________________________
> Wiki-research-l mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>
_______________________________________________
Wiki-research-l mailing list
[hidden email]
https://lists.wikimedia.org/mailman/listinfo/wiki-research-l