Difference between revisions of "Fake"
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== [http://www.emergent.info/ Emergent] == | == [http://www.emergent.info/ Emergent] == | ||
* [http://www.craigsilverman.ca/ Craig Silverman] | * [http://www.craigsilverman.ca/ Craig Silverman] | ||
| + | * [http://datajournalism.com/read/handbook/verification-3 Verification Handbook - For Disinformation And Media Manipulation | DataJournalism.com] | ||
* [http://www.buzzfeednews.com/author/craigsilverman BuzzFeed News] | * [http://www.buzzfeednews.com/author/craigsilverman BuzzFeed News] | ||
* [http://www.newsweek.com/radio-host-craig-silverman-fired-criticizing-trump-1472236 Radio Host Craig Silverman Says He Was Fired Mid-Show For Criticizing Trump: 'I See Corruption and Blatant Dishonesty' | Khaleda Rahman] | * [http://www.newsweek.com/radio-host-craig-silverman-fired-criticizing-trump-1472236 Radio Host Craig Silverman Says He Was Fired Mid-Show For Criticizing Trump: 'I See Corruption and Blatant Dishonesty' | Khaleda Rahman] | ||
Revision as of 05:58, 12 July 2020
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- Generative Adversarial Network (GAN)
- News sections
- The new AI tools spreading fake news in politics and business | Hannah Murphy - Financial Times
Disinformation — the deliberate spreading of false narratives through news, email and social media
Solving the Problem
Emergent
- Craig Silverman
- Verification Handbook - For Disinformation And Media Manipulation | DataJournalism.com
- BuzzFeed News
- Radio Host Craig Silverman Says He Was Fired Mid-Show For Criticizing Trump: 'I See Corruption and Blatant Dishonesty' | Khaleda Rahman
- Emergent: a novel data-set for stance classification | William Ferreira and Andreas Vlachos a new realworld dataset derived from the digital journalism project Emergent
- Emergent.info Blog
Emergent is part of a research project with the Tow Center for Digital Journalism at Columbia University that focuses on how unverified information and rumor are reported in the media. It aims to develop best practices for debunking misinformation.
Emergent | Craig Silverman and Adam Hooper - A real-time rumor tracker
So how does Emergent work? Silverman and a research assistant comb through social media and news websites using a variety of feeds, alerts and filters, and then enter claims that need debunking into the database and assign what Silverman calls a “truthiness” rating that marks each report as supporting the claim (i.e. stating it to be true), debunking it in some way or simply repeating it.
At that point, an algorithm takes over, and watches the URLs of the stories or posts that Silverman and his assistant entered into the database to see whether the content has been changed — that is, updated with a correction or some evidence that suggests it’s true or false. If there’s enough evidence, the status of the claim is changed, but that decision is always made by a human.