«Κυνηγούς» ψευδών ειδήσεων ετοιμάζουν οι Βρυξέλλες | Κόσμος | Η ΚΑΘΗΜΕΡΙΝΗ

Συμφωνήθηκε η ίδρυση δικτύου για τον εντοπισμό «όπλων προπαγάνδας» που αποκρύπτουν ορθές πληροφορίες.

Source: «Κυνηγούς» ψευδών ειδήσεων ετοιμάζουν οι Βρυξέλλες | Κόσμος | Η ΚΑΘΗΜΕΡΙΝΗ

Wikipedia criticised after it emerges female Nobel laureate had page rejected | The Independent

The Canadian scientist Donna Strickland is an associate professor of physics and astronomy at the University of Waterloo, a former president of the Optical Society and as of Tuesday, one of the winners of the 2018 Nobel Prize in Physics.  But until the hours after Ms Strickland’s win, the physicist did not have her own Wikipedia page as she was not considered significant enough.

Source: Wikipedia criticised after it emerges female Nobel laureate had page rejected | The Independent

Research Finds Bots and Russian Trolls Influenced Vaccine Discussion on Twitter | Office of Media Relations | The George Washington University

Social media bots and Russian trolls promoted discord and spread false information about vaccines on Twitter, according to new research led by the George Washington University. Using tactics similar to those at work during the 2016 United States presidential election, these Twitter accounts entered into vaccine debates months before election season was underway.

Source: Research Finds Bots and Russian Trolls Influenced Vaccine Discussion on Twitter | Office of Media Relations | The George Washington University

Fake news detector algorithm works better than a human | University of Michigan News

ANN ARBOR—An algorithm-based system that identifies telltale linguistic cues in fake news stories could provide news aggregator and social media sites like Google News with a new weapon in the fight against misinformation.

The University of Michigan researchers who developed the system have demonstrated that it’s comparable to and sometimes better than humans at correctly identifying fake news stories.

In a recent study, it successfully found fakes up to 76 percent of the time, compared to a human success rate of 70 percent. In addition, their linguistic analysis approach could be used to identify fake news articles that are too new to be debunked by cross-referencing their facts with other stories.

Source: Fake news detector algorithm works better than a human | University of Michigan News