Has machine learning identified the founders of the QAnon movement?

(Image Courtesy: Reuters)

Using Machine Learning, two separate teams of forensic linguists have claimed that they have discovered the origins of the QAnon mass political movement.

Often referred to as a cult, QAnon has spread various conspiracy theories about everything from Pizzagate, that accused a pizzeria of sexually abusing children, to claiming that former US President Donald Trump was targeted by an elite group made up of hollywood actors, politicians, tycoons and medical professionals.

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As The New York Times reported, two teams of Swiss and French computer scientists identified Paul Furber, a South African software developer as the first to post conspiracy theories using the handle before Arizona congressional candidate Ron Watkins took over the handle and started posting theories himself.

The Swiss team used machine learning to study QAnon's posts by breaking them down into patterns of three-character sequences. Then these sequences were checked against the posts, to see how often the patterns repeated. The French team fed the posts through AI, to look for identifiable patterns in writing. Both teams limited the scope of the investigation to social media posts made from the handle.

“At first most of the text is by Furber,” said Florian Cafiero from the French team.

“But the signature of Ron Watkins increased during the first few months as Paul Furber decreased and then dropped completely,” he added.

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So far, both Furber and Watkins have denied involvement with the movement, with Furber claiming he was simply influenced by the writing style of Q's posts.

"I am not Q," said Watkins, when approached by The New York Times for comment.