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 <http://www.nytimes.com/2016/11/20/business/media/how-fake-news-spreads.html?hp&action=click&pgtype=Homepage&clickSource=story-heading&module=b-lede-package-region&region=top-news&WT.nav=top-news>


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 <[email protected]> on behalf of Joe Spinden <[email protected]>
*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 <[email protected]> on behalf of Joe Spinden <[email protected]>
*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
to unsubscribehttp://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIChttp://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

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