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[CM] Troll spotting algorithm

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  [CM] Troll spotting algorithm RS Wood  <rsw@therandymon.com> - 2015-04-14 14:52 +0000
    Re: [CM] Troll spotting algorithm Dan Espen <despen@verizon.net> - 2015-04-14 14:02 -0400
      Re: [CM] Troll spotting algorithm Hils <hils@saynotospam.net> - 2015-04-14 19:19 +0100
        Re: [CM] Troll spotting algorithm Dan Espen <despen@verizon.net> - 2015-04-14 14:28 -0400
          Re: [CM] Troll spotting algorithm Hils <hils@saynotospam.net> - 2015-04-14 22:11 +0100
            Re: [CM] Troll spotting algorithm RS Wood <rsw@therandymon.com> - 2015-04-15 11:26 +0000
              Re: [CM] Troll spotting algorithm Bud Frede <frede@mouse-potato.com> - 2015-04-23 12:42 -0400
    Re: [CM] Troll spotting algorithm Shadow <Sh@dow.br> - 2015-04-14 17:20 -0300
    Re: [CM] Troll spotting algorithm Andy Burns <usenet.feb2014@adslpipe.co.uk> - 2015-04-14 22:10 +0100
    Re: [CM] Troll spotting algorithm Bruce Horrocks <07.013@scorecrow.com> - 2015-04-15 11:02 +0100
      Re: [CM] Troll spotting algorithm Dan Espen <despen@verizon.net> - 2015-04-15 11:45 -0400
    Re: [CM] Troll spotting algorithm Sylvia Else <sylvia@not.at.this.address> - 2015-04-16 23:15 +1000
    Re: [CM] Troll spotting algorithm Bud Frede <frede@mouse-potato.com> - 2015-04-23 12:30 -0400

#7383 — [CM] Troll spotting algorithm

From the «none of that here» department:
Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
Author:
Date: Sat, 11 Apr 2015 07:04:46 -0400
Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1

A group of Stanford computer scientists have developed an algorithm that
supposedly can detect trolls by analyzing as few as five comments . Today,
Justin Cheng at Stanford University in California and a few pals say they have
created just such a tool by analyzing the behavior of trolls on several
well-known websites and creating an algorithm that can accurately spot them
after as few as 10 posts.


--
Posting to comp.misc, sci.misc, and misc.news.internet.discuss

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#7387

RS Wood  <rsw@therandymon.com> writes:

> From the «none of that here» department:
> Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
> Author:
> Date: Sat, 11 Apr 2015 07:04:46 -0400
> Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1
>
> A group of Stanford computer scientists have developed an algorithm that
> supposedly can detect trolls by analyzing as few as five comments . Today,
> Justin Cheng at Stanford University in California and a few pals say they have
> created just such a tool by analyzing the behavior of trolls on several
> well-known websites and creating an algorithm that can accurately spot them
> after as few as 10 posts.

I look forward to the day said algorithm becomes part of Usenet.
With all it's warts, it's better than what we face now.

-- 
Dan Espen

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#7388

On 14/04/15 19:02, Dan Espen wrote:
> RS Wood  <rsw@therandymon.com> writes:
> 
>> From the «none of that here» department:
>> Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
>> Author:
>> Date: Sat, 11 Apr 2015 07:04:46 -0400
>> Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1
>>
>> A group of Stanford computer scientists have developed an algorithm that
>> supposedly can detect trolls by analyzing as few as five comments . Today,
>> Justin Cheng at Stanford University in California and a few pals say they have
>> created just such a tool by analyzing the behavior of trolls on several
>> well-known websites and creating an algorithm that can accurately spot them
>> after as few as 10 posts.
> 
> I look forward to the day said algorithm becomes part of Usenet.
> With all it's warts, it's better than what we face now.

It's only a matter of time before someone uses the algorithm to produce
trollbots.

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#7389

Hils <hils@saynotospam.net> writes:

> On 14/04/15 19:02, Dan Espen wrote:
>> RS Wood  <rsw@therandymon.com> writes:
>> 
>>> From the «none of that here» department:
>>> Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
>>> Author:
>>> Date: Sat, 11 Apr 2015 07:04:46 -0400
>>> Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1
>>>
>>> A group of Stanford computer scientists have developed an algorithm that
>>> supposedly can detect trolls by analyzing as few as five comments . Today,
>>> Justin Cheng at Stanford University in California and a few pals say they have
>>> created just such a tool by analyzing the behavior of trolls on several
>>> well-known websites and creating an algorithm that can accurately spot them
>>> after as few as 10 posts.
>> 
>> I look forward to the day said algorithm becomes part of Usenet.
>> With all it's warts, it's better than what we face now.
>
> It's only a matter of time before someone uses the algorithm to produce
> trollbots.

And the ensuing battles will be known as the Troll Wars.

-- 
Dan Espen

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#7395

On 14/04/15 19:28, Dan Espen wrote:
> Hils <hils@saynotospam.net> writes:
> 
>> On 14/04/15 19:02, Dan Espen wrote:
>>> RS Wood  <rsw@therandymon.com> writes:
>>>
>>>> From the «none of that here» department:
>>>> Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
>>>> Author:
>>>> Date: Sat, 11 Apr 2015 07:04:46 -0400
>>>> Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1
>>>>
>>>> A group of Stanford computer scientists have developed an algorithm that
>>>> supposedly can detect trolls by analyzing as few as five comments . Today,
>>>> Justin Cheng at Stanford University in California and a few pals say they have
>>>> created just such a tool by analyzing the behavior of trolls on several
>>>> well-known websites and creating an algorithm that can accurately spot them
>>>> after as few as 10 posts.
>>>
>>> I look forward to the day said algorithm becomes part of Usenet.
>>> With all it's warts, it's better than what we face now.
>>
>> It's only a matter of time before someone uses the algorithm to produce
>> trollbots.
> 
> And the ensuing battles will be known as the Troll Wars.

It could be a way of developing AI systems, with troll bots and troll
detectives playing cat and mouse among the human population, scoring
points for evading detection or soliciting human replies, losing points
for false accusations. They could be the Turing Troll Wars.

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#7402

On 2015-04-14, Hils <hils@saynotospam.net> wrote:
>> And the ensuing battles will be known as the Troll Wars.
>
> It could be a way of developing AI systems, with troll bots and troll
> detectives playing cat and mouse among the human population, scoring
> points for evading detection or soliciting human replies, losing
> points for false accusations. They could be the Turing Troll Wars.

That would make this classic XKCD germane:
https://xkcd.com/810/

"Spammers are breaking traditional captchas with AI, so I've built a new
system.  It asks users to rate a slate of comments as 'constructive' or
'not constructive' ... "

I /do/ miss the days of really clever trolling: subtle remarks designed
to casually cause a conflagration.  These days so much of it is simple
ass-hattery.

I thought a bit about what this type of algorithm would look like: the
science ought to be something like Bayesian filtering, probabilities of
word order, and so on.  But it's hard to pick out sarcasm, nuances of
humor, and the like.  Post length is no easy indicator.  No single
vocabulary word gives it away.  IP address might help these days now
that so few are on dial-up and user addresses stay the same for longer.
On Usenet, user name often helps (ignore any post from a user named
"obamasucks@donkeyballs.org" or whatever on the grounds a fake ID with
an inflammatory address is likely to be out to stir the pot?).  You
could look for patterns of a user consistently replying after a post
about certain subjects (which would draw out the single-issue haters).
Beyond that, this isn't easy stuff and I'd think the false-positives
would be ridiclous. 

There are frequent, long discussions on soylentnews about how to tweak
the karma and scoring algorithms, but it always comes down to users
trying to adjust the math so they hear only from people they want to and
are barred from seeing posts from people they don't want to hear from.
Usenet, for all its shortcomings, does away with the issue by letting
anyone post anything and leaving it to the user with his killfile and
filters to sort out the damage.  Maybe the only way to win the game is
not to play it ...

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#7479

RS Wood <rsw@therandymon.com> writes:

>
> There are frequent, long discussions on soylentnews about how to tweak
> the karma and scoring algorithms, but it always comes down to users
> trying to adjust the math so they hear only from people they want to and
> are barred from seeing posts from people they don't want to hear from.
> Usenet, for all its shortcomings, does away with the issue by letting
> anyone post anything and leaving it to the user with his killfile and
> filters to sort out the damage.  Maybe the only way to win the game is
> not to play it ...

"Be liberal in what you accept, and conservative in what you send" - Jon
Postel

According to that, what we need is more conservative trolls, not less
liberal readers. :)

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#7390

On Tue, 14 Apr 2015 14:52:42 +0000 (UTC), RS Wood
<rsw@therandymon.com> wrote:

>From the «none of that here» department:
>Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
>Author:
>Date: Sat, 11 Apr 2015 07:04:46 -0400
>Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1
>
>A group of Stanford computer scientists have developed an algorithm that
>supposedly can detect trolls by analyzing as few as five comments . Today,
>Justin Cheng at Stanford University in California and a few pals say they have
>created just such a tool by analyzing the behavior of trolls on several
>well-known websites and creating an algorithm that can accurately spot them
>after as few as 10 posts.

	So that's what all those spots were. I thought I'd come down
with measles !!
	;)
	[]'s
-- 
Don't be evil - Google 2004
We have a new policy  - Google 2012

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#7394

RS Wood wrote:

> Justin Cheng at Stanford University in California and a few pals say they have
> created just such a tool by analyzing the behavior of trolls on several
> well-known websites and creating an algorithm that can accurately spot them
> after as few as 10 posts.

Maybe the standard of trolls on usenet is dropping, many of the 
nymshifters are identifiable after just one post ...

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#7399

On 14/04/2015 15:52, RS Wood wrote:
>  From the «none of that here» department:

 From the 'oh the irony' department:

> Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
> Author:
> Date: Sat, 11 Apr 2015 07:04:46 -0400
> Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1
>
> A group of Stanford computer scientists have developed an algorithm that
> supposedly can detect trolls by analyzing as few as five comments . Today,
                                                       ^^^^
> Justin Cheng at Stanford University in California and a few pals say they have
> created just such a tool by analyzing the behavior of trolls on several
> well-known websites and creating an algorithm that can accurately spot them
> after as few as 10 posts.
                   ^^

So is it 5 or 10? Typical troll behaviour. ;-)

-- 
Bruce Horrocks
Surrey
England
(bruce at scorecrow dot com)

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#7403

Bruce Horrocks <07.013@scorecrow.com> writes:

> On 14/04/2015 15:52, RS Wood wrote:
>>  From the «none of that here» department:
>
> From the 'oh the irony' department:
>
>> Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
>> Author:
>> Date: Sat, 11 Apr 2015 07:04:46 -0400
>> Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1
>>
>> A group of Stanford computer scientists have developed an algorithm that
>> supposedly can detect trolls by analyzing as few as five comments . Today,
>                                                      ^^^^
>> Justin Cheng at Stanford University in California and a few pals say they have
>> created just such a tool by analyzing the behavior of trolls on several
>> well-known websites and creating an algorithm that can accurately spot them
>> after as few as 10 posts.
>                  ^^
>
> So is it 5 or 10? Typical troll behaviour. ;-)

Appears to be:

5 = supposedly detect
10 = accurately spot

Assume there is a smiley right about here...

-- 
Dan Espen

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#7415

On 15/04/2015 12:52 AM, RS Wood wrote:
>  From the «none of that here» department:
> Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
> Author:
> Date: Sat, 11 Apr 2015 07:04:46 -0400
> Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1
>
> A group of Stanford computer scientists have developed an algorithm that
> supposedly can detect trolls by analyzing as few as five comments . Today,
> Justin Cheng at Stanford University in California and a few pals say they have
> created just such a tool by analyzing the behavior of trolls on several
> well-known websites and creating an algorithm that can accurately spot them
> after as few as 10 posts.

On has to wonder how they validate their data.

After all, before one can check the algorithm, one has to have some 
other way of identifying trolls.

A more accurate statement of the accomplishment would be that the 
scientists have created an algorithm that replicates their own 
assessment of who is a troll.

Sylvia.

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#7477

RS Wood  <rsw@therandymon.com> writes:

> From the «none of that here» department:
> Title: Stanford Computer Scientists Develop "Troll-Spotting Algorithm,"...
> Author:
> Date: Sat, 11 Apr 2015 07:04:46 -0400
> Link: http://www.topix.net/science/computer-science/2015/04/1504119NENVT?fromrss=1
>
> A group of Stanford computer scientists have developed an algorithm that
> supposedly can detect trolls by analyzing as few as five comments . Today,
> Justin Cheng at Stanford University in California and a few pals say they have
> created just such a tool by analyzing the behavior of trolls on several
> well-known websites and creating an algorithm that can accurately spot them
> after as few as 10 posts.
>

In my misspent youth I would have liked an algorithm for spotting
trollops. (Take that whichever way you like.) :)

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