Friam

Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

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Joe Spinden

Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

For discussion ??:

http://www.nytimes.com/2016/11/18/technology/automated-pro-trump-bots-overwhelmed-pro-clinton-messages-researchers-say.html

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Joe

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Marcus G. Daniels

Re: Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

"[..] with a bit of [artificial] intelligence and rudimentary communication skills"

Right tool for that job.. But how do you build an army of bots that can enlighten instead of just confuse?

Marcus

From: Friam <[hidden email]> on behalf of Joe Spinden <[hidden email]>
Sent: Sunday, November 20, 2016 11:12:04 AM
To: The Friday Morning Applied Complexity Coffee Group
Subject: [FRIAM] Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

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Joe Spinden

Re: Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

Not sure that is possible. But I would be happy with identifying and responding in real time.. Not thrilled to think the elections here and elsewhere are swayed by automated misinformation..

Joe

On 11/20/16 12:49 PM, Marcus Daniels wrote:

"[..] with a bit of [artificial] intelligence and rudimentary communication skills"

Right tool for that job.. But how do you build an army of bots that can enlighten instead of just confuse?

Marcus

From: Friam [hidden email] on behalf of Joe Spinden [hidden email]
Sent: Sunday, November 20, 2016 11:12:04 AM
To: The Friday Morning Applied Complexity Coffee Group
Subject: [FRIAM] Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

For discussion ??:

http://www.nytimes.com/2016/11/18/technology/automated-pro-trump-bots-overwhelmed-pro-clinton-messages-researchers-say.html

--
Joe

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FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
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FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

-- 
Joe

Marcus G. Daniels

Re: Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

Another approach might be to have signature based scanning, kind of like virus scanners or SPAM filters.

One might imagine using natural language processing to normalize tweet or Facebook excerpts into the same `meme' object, and then require Twitter, Facebook, etc. by law to highlight those meme objects that have been shown to be controversial or false, linking to background documents. Like http://www.nytimes.com/2016/11/20/business/media/how-fake-news-spreads.html

Multimedia objects (like the pictures above of the buses) would be an even easier way to spot variant instances of the same thing. Photoshop manipulations could probably be identified by automated means.

Authors with the intent to falsify news would probably switch between identities, so quantitative metrics on writing style or statistical patterns in target selection might be one way to identify culprits.

The databases of bad content and bad actors ought to be open source, so that it can be elaborated by anyone with the time and energy to do the research.

Marcus

From: Friam <[hidden email]> on behalf of Joe Spinden <[hidden email]>
Sent: Sunday, November 20, 2016 5:54:56 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

Not sure that is possible. But I would be happy with identifying and responding in real time.. Not thrilled to think the elections here and elsewhere are swayed by automated misinformation..

Joe

On 11/20/16 12:49 PM, Marcus Daniels wrote:

"[..] with a bit of [artificial] intelligence and rudimentary communication skills"

Right tool for that job.. But how do you build an army of bots that can enlighten instead of just confuse?

Marcus

From: Friam [hidden email] on behalf of Joe Spinden [hidden email]
Sent: Sunday, November 20, 2016 11:12:04 AM
To: The Friday Morning Applied Complexity Coffee Group
Subject: [FRIAM] Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

For discussion ??:

http://www.nytimes.com/2016/11/18/technology/automated-pro-trump-bots-overwhelmed-pro-clinton-messages-researchers-say.html

--
Joe

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

-- 
Joe

Joe Spinden

Re: Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

The technical part seems reasonable. I certainly like the idea of open source databases. The "by law" part is unrealistic, unless you can find a way to tie it into large tax breaks for the top 0.01%. Facebook/Twitter/etc. could do something like that, if they wanted to put resources on it. Whether they will or not is a different question. For now they seem to be in Denial (NOT the river in Egypt).

Joe

On 11/20/16 6:24 PM, Marcus Daniels wrote:

Another approach might be to have signature based scanning, kind of like virus scanners or SPAM filters.

One might imagine using natural language processing to normalize tweet or Facebook excerpts into the same `meme' object, and then require Twitter, Facebook, etc. by law to highlight those meme objects that have been shown to be controversial or false, linking to background documents. Like http://www.nytimes.com/2016/11/20/business/media/how-fake-news-spreads.html

Multimedia objects (like the pictures above of the buses) would be an even easier way to spot variant instances of the same thing. Photoshop manipulations could probably be identified by automated means.

Authors with the intent to falsify news would probably switch between identities, so quantitative metrics on writing style or statistical patterns in target selection might be one way to identify culprits.

The databases of bad content and bad actors ought to be open source, so that it can be elaborated by anyone with the time and energy to do the research.

Marcus

From: Friam [hidden email] on behalf of Joe Spinden [hidden email]
Sent: Sunday, November 20, 2016 5:54:56 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say
Not sure that is possible. But I would be happy with identifying and responding in real time.. Not thrilled to think the elections here and elsewhere are swayed by automated misinformation..

Joe

On 11/20/16 12:49 PM, Marcus Daniels wrote:
"[..] with a bit of [artificial] intelligence and rudimentary communication skills"

Right tool for that job.. But how do you build an army of bots that can enlighten instead of just confuse?

Marcus

From: Friam [hidden email] on behalf of Joe Spinden [hidden email]
Sent: Sunday, November 20, 2016 11:12:04 AM
To: The Friday Morning Applied Complexity Coffee Group
Subject: [FRIAM] Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

For discussion ??:

http://www.nytimes.com/2016/11/18/technology/automated-pro-trump-bots-overwhelmed-pro-clinton-messages-researchers-say.html

--
Joe

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
-- 
Joe
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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Joe

Steve Smith

Re: Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

In reply to this post by Joe Spinden

Joe -

I tried to read the original article, but it seems I've exceeded my 10 free articles for the month and need to sign up for a subscription. I'm literally holding my $6.00 paper copy of today's NYT of course... and they don't OFFER home delivery where I live (I've tried, they always botch it).

That whine out of my system, I have been spammed by e-mails for well over a year with Trump's name in the subject line... they are *mostly* oblique... not direct appeals, but rather gobbledeygook like "THIS is the personal defense tool Trumps Bodyguards carry!", etc. The very few messages with Hillary's name in the subject line were blatant smears against her, but they comprised less than 10% of that junk. I rarely open any of those messages and I think I can say that I *never* followed any links from them. They were just such blatant horseshit. Of course, the net effect on my contrarian self was to be way OVER him long before I suppose some other self-ascribed anarcho-libertarians might have been.

I got a modest amount of high-signal/noise Bernie mail and since I signed up for Jill and Gary, got a slightly higher volume of relatively high signal/noise mail from that quarter too. I don't think I saw a single piece of smear aimed at any of those three, either directly or by allusion.

I'm afraid that MANY do respond to this class of junk-mail... simple name recognition? Trump started with pretty high name recognition and the media just pumped his name continuously. Not to mention all of US whining and sneering his name out over and over and over.

I don't care for *any* automated swaying of the vote, even if what seems to be purveyed is (pro?)information? One blokes pro-information is another's mis-information I fear. "Push" media is just the wrong mechanism (IMO) for this kind of stuff. But then maybe our pop culture has us SO broken and bent that we *can't* handle using *pull* media? Everything needs to come to us in a stream whether we ask for it or not?

Just sayin'

- Steve

Not sure that is possible. But I would be happy with identifying and responding in real time.. Not thrilled to think the elections here and elsewhere are swayed by automated misinformation..

Joe

On 11/20/16 12:49 PM, Marcus Daniels wrote:
"[..] with a bit of [artificial] intelligence and rudimentary communication skills"

Right tool for that job.. But how do you build an army of bots that can enlighten instead of just confuse?

Marcus

From: Friam [hidden email] on behalf of Joe Spinden [hidden email]
Sent: Sunday, November 20, 2016 11:12:04 AM
To: The Friday Morning Applied Complexity Coffee Group
Subject: [FRIAM] Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

For discussion ??:

http://www.nytimes.com/2016/11/18/technology/automated-pro-trump-bots-overwhelmed-pro-clinton-messages-researchers-say.html

--
Joe

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
-- 
Joe
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Steve Smith

Re: Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

In reply to this post by Joe Spinden

Marcus -

I'd be interested in more detail on this concept as you reference it. I'm maybe more interested in simply "mapping it out" and letting the unwashed (or semi-washed) masses sort it out as they will.

I was so fascinated with the idea exemplified by the (now very old) NewsMap
http://newsmap.jp/
that when I participated in an Annenberg "Vectors" (now defunct) workshop at USC years ago, I sketched out and proposed a project to apply our (joint project with UNM) FROTH (force-directed Recursive layout Of Tree Hierarchies) to a live Yahoo or Google Newsfeed.

What you see above is a snapshot of a dynamic layout ( in this case the DNS addresses of hosts "attacking" the LANL open network ) which bubbles and froths as new connections come in. What I proposed was a 3D extrusion of the same, so that in place of each "circle" there would be a tendril/tube growing from nothing (beginning of a story) and eventually shrinking to nothing again when the story died out.

NewsMap has a metric for "sameness" to indicate which stories are really the "same" as other stories, but on inspection it seems pretty lame. I'd much rather do this in a derived "meme space" than "headline space" and I suppose the Tweet-o-sphere is the current key digital swamp to consider highest importance/frequency/impact/???

I predict we would see features in this space including wag-the-dog-esque diversionary stories... my (ex) sister-in-law who works inside the belly of the (other) beast (DNC strategist) admitted that *every day* they struggle to make sure certain stories occur "below the fold" on the front page of critical papers... they just need to shove things down about 3-5 stories to keep them from showing up as "above the fold" headlines... and THAT is such a big win, they barely care about the rest!

The technical part seems reasonable. I certainly like the idea of open source databases. The "by law" part is unrealistic, unless you can find a way to tie it into large tax breaks for the top 0.01%. Facebook/Twitter/etc. could do something like that, if they wanted to put resources on it. Whether they will or not is a different question. For now they seem to be in Denial (NOT the river in Egypt).

Joe

On 11/20/16 6:24 PM, Marcus Daniels wrote:
Another approach might be to have signature based scanning, kind of like virus scanners or SPAM filters.

One might imagine using natural language processing to normalize tweet or Facebook excerpts into the same `meme' object, and then require Twitter, Facebook, etc. by law to highlight those meme objects that have been shown to be controversial or false, linking to background documents. Like http://www.nytimes.com/2016/11/20/business/media/how-fake-news-spreads.html

Multimedia objects (like the pictures above of the buses) would be an even easier way to spot variant instances of the same thing. Photoshop manipulations could probably be identified by automated means.

Authors with the intent to falsify news would probably switch between identities, so quantitative metrics on writing style or statistical patterns in target selection might be one way to identify culprits.

The databases of bad content and bad actors ought to be open source, so that it can be elaborated by anyone with the time and energy to do the research.

Marcus

From: Friam [hidden email] on behalf of Joe Spinden [hidden email]
Sent: Sunday, November 20, 2016 5:54:56 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say
Not sure that is possible. But I would be happy with identifying and responding in real time.. Not thrilled to think the elections here and elsewhere are swayed by automated misinformation..

Joe

On 11/20/16 12:49 PM, Marcus Daniels wrote:
"[..] with a bit of [artificial] intelligence and rudimentary communication skills"

Right tool for that job.. But how do you build an army of bots that can enlighten instead of just confuse?

Marcus

From: Friam [hidden email] on behalf of Joe Spinden [hidden email]
Sent: Sunday, November 20, 2016 11:12:04 AM
To: The Friday Morning Applied Complexity Coffee Group
Subject: [FRIAM] Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

For discussion ??:

http://www.nytimes.com/2016/11/18/technology/automated-pro-trump-bots-overwhelmed-pro-clinton-messages-researchers-say.html

--
Joe

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
-- 
Joe
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
-- 
Joe
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Marcus G. Daniels

Re: Automated Pro-Trump Bots Overwhelmed Pro-Clinton Messages, Researchers Say

Steve writes:

"I'd be interested in more detail on this concept as you reference it.

In an early form, one might:

1) Take fact checking websites like WaPost's and encode the claims in a language like CycL. This would be a human curated database, tuned by ontologists and journalists. It would be exposed through a client library that anyone could use.

2) A company like Twitter would make call to this library to invoke a natural language parser to turn tweets (near raw text of not quite English) into propositions in first order logic.

3) Before rendering text as XML/HTML, they would invoke a logic engine via a library call to satisfy the propositions from #2 using the database in #1. The library could add attributes to the XML and some simple CSS rules could control how it was shown in the users' web browser.

The Washington Post talks about shading of facts, selective telling of the the truth, and use of legalistic language as determinants in rating truthiness. One way to do this would be to have #1 built into typically-observed sets of clauses -- frequently observed claims that people repeat without significant embellishment. "Hillary says the working white are deplorable" would be a low truthiness tweet whereas "Hillary says some Trump voters are racist or misogynist and others are frustrated because nobody cares about them" would be a higher truthiness because the latter captures more of the original text. The truthiness could be communicated by suppressing text when it was >= 3 Pinocchios, forcing the user to click on an icon to reveal the original nonsense. Of course, the natural language processing would have to be pretty good at normalizing propositions into a form consistent with the database, and the database would need to be up-to-date with the candidates' various public statements.

Marcus