A New York Times special report says that two teams of experts have come to the same conclusion and unmasked the identities of QAnon using artificial intelligence. The infamous QAnon movement is centered on the mysterious Q posts that spread false, bizarre and radical far-right political conspiracy theories. In addition, the movement is linked to misinformation and violence in the Capital Riots.
Some describe QAnon as a cult. Other experts say it is a manipulation of the masses to destabilize the government. QAnon conspiracy theories range from Satanic presences in the highest spheres of government to cannibalistic pedophiles operating a global child sex trafficking ring from Washington D.C.
The New York Times reported that two independent teams of forensic linguistic experts had used AI to analyze the texts of Q and revealed who was behind the inflammatory posts. Both studies concluded that Paul Furber, a South African software developer and tech journalist, is one of the original Q posts authors. Both teams also identified the Arizona congressional candidate Ron Watkins. They say he wrote under the Q pseudonym, first collaborating with Furber, and later took over.
How They Used AI To Unmask Q
The two teams, one Swiss and the other French, worked independently to reveal Q's identity. The Swiss team, made up of two researchers from OrphAnalytics, used special software to detect identifiable "variations" in text. The approach is known as stylometry, and researchers ran it as a mathematical algorithm. The software broke down Q's texts into patterns of three-character sequences and tracked the recurrence of each possible combination. The team says their accuracy is 93 percent correct.
On the other hand, the French team says their study correctly identified Mr. Watking with 99 percent certainty and Mr. Furber with 98 percent. They trained an AI to look for patterns in Q's texts. Both teams used stylometry approaches. The FBI has used stylometry to identify Ted Kaczynski as the Unabomber. It has also been used in numerous law enforcement cases with success. More than 100,000 words by Q and about 12,000 words from 13 compared writers were analyzed.
The New York Times reports that David Hoover, an English professor at New York University and an expert in author identification, concludes the study is "quite persuasive." Other experts agreed with the studies. Furber and Watkins both denied having written Q's messages. Furber says the reason why the AI came up with these results was that his writing was influenced by Q's posts, a fact a linguistic expert says is "implausible." Millions of people still believe in the QAnon movement. Researchers told the press they hoped to unmask Q to "loosen QAnon's hold on the people."
Source: New York Times