Title: Machine learning potentially identifies the masterminds behind the viral movement - QAnon by David D. Kirkpatrick (NYTimes, Feb 19, 2022)
Two teams of forensic linguists used machine learning to identify Paul Furber and Ron Watkins as likely authors of the messages that fueled QAnon – a set of internet conspiracy theories that falsely allege the world is run by a cabal of Satan-worshiping pedophiles (NYTimes). The two teams, one Swiss and one French, used different techniques of stylometry to identify common patterns that a casual reader could not detect on their own. This is powerful, according to Dr. Patrick Juola of Duquesne University, as it proves that their method is measurable, consistent, and replicable. Scientists who conducted the studies said that they hoped unmasking the creators might weaken their hold over QAnon followers.