I am going to quote Joseph Reagle, who responded to a similarly titled
threat on Wiki-en-L:
date:13 November 2015 at 13:48
It's been great that Riot games has had someone like Lin (an experimental
psychologist) to think about issues of community and abuse. And I
appreciate that Lin has been previously been so forthcoming about their
experiences and findings.
But the much trumpeted League of Legends Tribunal has been down "for
maintenance" for months, even before this article was published, with much
discussion by the community of how it was broken. On this, Riot and Lin
have said nothing.
Copying Joseph in case he wants to respond to some of the discussions here.
Risker/Anne
On 15 November 2015 at 10:36, Pharos <pharosofalexandria(a)gmail.com> wrote:
The figure quoted is quite interesting, but do we have
a comparable metric
for the Wikimedia projects? :
"... incidences of homophobia, sexism and racism ... have fallen to a
combined
2 percent of all games"
2% sounds "low", but do we indeed know if this is better or worse than us?
Would our comparable metric be the % of bigoted comments per article, per
talk page discussion, per time that an editor spends at the project? I
would think that encountering bigoted comments on 1 in 50 discussions would
still be pretty significant.
Thanks,
Pharos
On Sun, Nov 15, 2015 at 1:21 PM, Ziko van Dijk <zvandijk(a)gmail.com> wrote:
Hello,
Just yesterday I had a long talk with a researcher about how to define
and detect trolls on Wikipedia. E.g., whether "unintentional trolling"
should be included or not.
In my opinion, it is not possible to detect by machine trollism,
unkindness, harassment, mobbing etc., maybe with the exception of
swear words. A lot of turntaking, deviation from the topic and other
phenomena can be experienced by the participants as positive or as
negative. You might need to ask them, and even then they might not be
aware of a problem that works through in subtlety. Also, third persons
not involved in the conversation can be effected negatively (look at
... page X... and you know why you don't like to contribute there).
Kind regards
Ziko
2015-11-15 17:40 GMT+01:00 Katherine Casey <fluffernutter.wiki(a)gmail.com
:
I'd be happy to offer my admin/oversighter
experience and knowledge to
help
> you develop the labeling and such, Aaron! I just commented on Andreas's
> proposal on the Community Wishlist, but to summarize here: I see a lot
of
potential
pitfalls in trying to handle/generalize this with machine
learning, but I also see a lot of potential value, and I think it's
something we should be investigating.
-Fluffernutter
On Sun, Nov 15, 2015 at 11:32 AM, Aaron Halfaker <
ahalfaker(a)wikimedia.org>
wrote:
> >
> > The League of Legends team collaborated with outside scientists to
> > analyse their dataset. I would love to see the Wikimedia Foundation
> engage
> > in a similar research project.
>
>
> Oh! We are! :) When we have time. :\ One of the projects that I'd
like
to
>> see done, but I've struggled to find the time for is a common talk
page
>
parser[1] that could produce a dataset of talk page interactions. I'd
like
>> this dataset to be easy to join to editor outcome measures. E.g.
there
> might
be "aggressive" talk that we don't know is problematic until we
see
>> the kind of effect that it has on other conversation participants.
>>
>> Anyway, I want some powerful utilities and datasets out there to help
>> academics look into this problem more easily. For revscoring, I'd
like
to
>> be able to take a set of talk page diffs, have them classified in Wiki
>> labels[2] as "aggressive" and the build a model for ORES[3] to be
used
>> however people see fit. You could then use ORES to do offline
analysis
of
> discussions for research. You could use ORES
to interrupt the a user
> before saving a change. I'm sure there are other clever ideas that
people
> have for what to do with such a model that
I'm happy to enable it via
the
>> service. The hard part is getting a good dataset labeled.
>>
>> If someone wants to invest some time and energy into this, I'm happy
to
> work
with you. We'll need more than programming help. We'll need a
lot of
> help to figure out what dimensions we'll
label talk page postings by
and to
> do the actual labeling.
>
> 1.
https://github.com/Ironholds/talk-parser
> 2.
https://meta.wikimedia.org/wiki/Wiki_labels
> 3.
https://meta.wikimedia.org/wiki/ORES
>
> On Sun, Nov 15, 2015 at 6:56 AM, Andreas Kolbe <jayen466(a)gmail.com>
wrote:
>>
>> > On Sat, Nov 14, 2015 at 9:13 PM, Benjamin Lees <
emufarmers(a)gmail.com>
>> > wrote:
>> >
>> > > This article highlights the happier side of things, but it appears
>> > > that Lin's approach also involved completely removing bad actors:
>> > > "Some players have also asked why we've taken such an
aggressive
>> > > stance when we've been focused on reform; well, the key here is
that
>> > > for most players, reform
approaches are quite effective. But, for
a
>> > > number of players, reform
attempts have been very unsuccessful
which
>> > > forces us to remove some of
these players from League
entirely."[0]
>> > >
>> >
>> >
>> > Thanks for the added context, Benjamin. Of course, banning bad
actors
> that
> > they consider unreformable is something Wikipedia admins have always
done
>> > as well.
>> >
>> > The League of Legends team began by building a dataset of
interactions
> that
> > the community considered unacceptable, and then applied
machine-learning
>> to
>> > that dataset.
>> >
>> > It occurs to me that the English Wikipedia has ready access to such
a
> >
dataset: it's the totality of revision-deleted and oversighted talk
page
> > posts. The League of Legends team
collaborated with outside
scientists to
> > analyse their dataset. I would love to
see the Wikimedia Foundation
> engage
> > in a similar research project.
> >
> > I've added this point to the community wishlist survey:
> >
> >
> >
>
https://meta.wikimedia.org/wiki/2015_Community_Wishlist_Survey#Machine-lear…
> >
> >
> >
> > > P.S. As Rupert noted, over 90% of LoL players are male (how much
over
> > > 90%?).[1] It would be interesting
to know whether this percentage
has
>> > > changed along with the improvements described in the article.
>> > >
>> >
>> >
>> > Indeed.
>> > _______________________________________________
>> > Wikimedia-l mailing list, guidelines at:
>> >
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines
>> > Wikimedia-l(a)lists.wikimedia.org
>> > Unsubscribe:
https://lists.wikimedia.org/mailman/listinfo/wikimedia-l
,
>> > <mailto:wikimedia-l-request@lists.wikimedia.org
?subject=unsubscribe>
>> >
>> _______________________________________________
>> Wikimedia-l mailing list, guidelines at:
>>
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines
>> Wikimedia-l(a)lists.wikimedia.org
>> Unsubscribe:
https://lists.wikimedia.org/mailman/listinfo/wikimedia-l ,
<mailto:wikimedia-l-request@lists.wikimedia.org?subject=unsubscribe>
--
Karen Brown
user:Fluffernutter
*Unless otherwise specified, any email sent from this address is in my
volunteer capacity and does not represent the views or wishes of the
Wikimedia Foundation*
_______________________________________________
Wikimedia-l mailing list, guidelines at:
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines
<mailto:wikimedia-l-request@lists.wikimedia.org?subject=unsubscribe>
_______________________________________________
Wikimedia-l mailing list, guidelines at:
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines
Wikimedia-l(a)lists.wikimedia.org
Unsubscribe:
https://lists.wikimedia.org/mailman/listinfo/wikimedia-l,
<mailto:wikimedia-l-request@lists.wikimedia.org?subject=unsubscribe>
_______________________________________________
Wikimedia-l mailing list, guidelines at:
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines
Wikimedia-l(a)lists.wikimedia.org
Unsubscribe:
https://lists.wikimedia.org/mailman/listinfo/wikimedia-l,
<mailto:wikimedia-l-request@lists.wikimedia.org?subject=unsubscribe>