USA: Hundreds of thousands created on Twitter bots that praise Trump and attack his opponents
Over the past 11 months, several hundred thousand fake, automated accounts, or bots, have been created on Twitter that praise former President Donald Trump and attack his opponents or potential rivals in the presidential election, the Associated Press reported on Monday.
Bots ridicule Trump critics among both Democrats and Republicans, multiply praise for the former president and attack former US ambassador to the UN Nikki Haley, who announced that she will seek the Republican nomination in the next presidential election, according to the agency that received materials on the about the bot network from the Israeli technology company Cyabra.
Cyabra detected the existence of a network of fake automated accounts that were created in large groups in April, October and November last year, which made their identification somewhat easier, as well as the constant repetition of the same content, which does not happen to “human users,” the AP explains.
In recent months, bots have “aggressively multiplied suggestions” that Florida Governor Ron DeStanis, who would be Trump’s particularly dangerous rival if he ran, has no chance of winning, but would be a very good candidate for Trump’s vice president.
Cyabra employees have not been able to determine who opened the fake accounts, but they believe that the bot network was created in the US.
Bots are supposed to publicize and duplicate the message, creating a false belief about Trump’s popularity or the number of his supporters; constant repetition of information is the main principle of propaganda, and bots are able to repeat it indefinitely – explains prof. Samuel Wooley of the University of Texas doing digital propaganda research.
Until recently, most fake, automated accounts were relatively easy to identify because they happened to post nonsense words or series of random numbers, but soon, thanks to the use of artificial intelligence, bots will become much more sophisticated and difficult to detect, warns the AP. )
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