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

2019-06-26 Thread 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  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 
> 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 
>>
>
>
> --
> Janna Layton (she, her)
> Administrative Assistant - Audiences & Technology
> Wikimedia Foundation 
>


-- 
Janna Layton (she, her)
Administrative Assistant - Audiences & Technology
Wikimedia Foundation 
___
Wikimedia-l mailing list, guidelines at: 
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and 
https://meta.wikimedia.org/wiki/Wikimedia-l
New messages to: Wikimedia-l@lists.wikimedia.org
Unsubscribe: https://lists.wikimedia.org/mailman/listinfo/wikimedia-l, 


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

2019-06-26 Thread AZ Mayank
Any wikipedia meetup or anything next month ? I want to participate from
Nepal ? Let me know?

Best,
Owlf

On Tue, Jun 25, 2019, 10:00 PM Janna Layton  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 
> 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 
> >
>
>
> --
> Janna Layton (she, her)
> Administrative Assistant - Audiences & Technology
> Wikimedia Foundation 
> ___
> Wikimedia-l mailing list, guidelines at:
> https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and
> https://meta.wikimedia.org/wiki/Wikimedia-l
> New messages to: Wikimedia-l@lists.wikimedia.org
> Unsubscribe: https://lists.wikimedia.org/mailman/listinfo/wikimedia-l,
> 
___
Wikimedia-l mailing list, guidelines at: 
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and 
https://meta.wikimedia.org/wiki/Wikimedia-l
New messages to: Wikimedia-l@lists.wikimedia.org
Unsubscribe: https://lists.wikimedia.org/mailman/listinfo/wikimedia-l, 

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

2019-06-25 Thread Janna Layton
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  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 
>


-- 
Janna Layton (she, her)
Administrative Assistant - Audiences & Technology
Wikimedia Foundation 
___
Wikimedia-l mailing list, guidelines at: 
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and 
https://meta.wikimedia.org/wiki/Wikimedia-l
New messages to: Wikimedia-l@lists.wikimedia.org
Unsubscribe: https://lists.wikimedia.org/mailman/listinfo/wikimedia-l, 


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

2019-06-24 Thread 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 
___
Wikimedia-l mailing list, guidelines at: 
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and 
https://meta.wikimedia.org/wiki/Wikimedia-l
New messages to: Wikimedia-l@lists.wikimedia.org
Unsubscribe: https://lists.wikimedia.org/mailman/listinfo/wikimedia-l,