Hidden racial slurs are flooding across Russian media, AI reveals
A glut of racial slurs hidden behind slang has emerged in Russian digital media.
The insults were discovered by Osavul, a Ukrainian startup that uses AI to analyse information threats.
Osavul tapped language models to conduct a cross-platform survey of racial discourse in Russia. Over 5,000 messages were scanned on news sites and social media platforms, from US giants Facebook and X to Russian kingpins Telegram and VK.
The system highlighted the rise of various epithets for neighbouring countries, immigrants, and national minorities. Even Kremlin officials were spotted using the slurs.
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Osavul said the vocabulary deliberately conceals the racial and ethnic undertones from foreign eyes.
“Russian slang helps to hide negative attitudes towards national minorities and immigrants inside Russia and gets hatred towards them in society,” Andrew Bevz, the startup’s chief marketing officer, told TNW.
The most widespread barb was “foreign specialist” (инностранный специалист). Used ironically, the term ridicules the qualifications and education levels of migrants.
Osavul also unearthed curious correlations between the slurs and current events.
Hidden in plain sight on Russian media
Neighbouring states were frequent targets of the insults. According to Osavul’s research, Russian neo-imperial discourse often depicts these nations as rebellious provinces and traitors.
A common example is using the phrase “on Ukraine” instead of “in Ukraine,” which implies the country is not truly independent.
Poland was also repeatedly denigrated. The AI system regularly detected the pejorative “psheks,” a Russian slur that imitates a common sound in spoken Polish.
The word’s prevalence aligned with political developments. Usage peaked after former Russian president Dmitry Medvedev posted the word on Telegram last August. It then spread across the internet.
Sightings of the term declined when Poland blockaded Ukrainian grain imports in September. Negativity towards Poles in Russian online spaces subsequently decreased.
Another emergent “dog whistle” is the use of “Abramovichs,” (Абрамовичи) “Galkins,” (Галкины) and “Chubaises” (Чубайсы).
All three words are taken from the surnames of prominent Russian Jews. By pluralising them, users equate Jewish origins with opposition to Russia.
Osavul also discovered mockery of the Soviet ideology of “friendship of nations.” Across online media, the term “multinational” (многнационал) and its derivates have now harnessed to criticise diversity.
These findings showcase AI’s potential to analyse online language. Bevz argues that they also expose a national trend.
“Russian society no longer believes in the ‘multicultural’ discourse inherited from the USSR and sold by the current government in the global arena,” he said.
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A glut of racial slurs hidden behind slang has emerged in Russian digital media.
The insults were discovered by Osavul, a Ukrainian startup that uses AI to analyse information threats.
Osavul tapped language models to conduct a cross-platform survey of racial discourse in Russia. Over 5,000 messages were scanned on news sites and social media platforms, from US giants Facebook and X to Russian kingpins Telegram and VK.
The system highlighted the rise of various epithets for neighbouring countries, immigrants, and national minorities. Even Kremlin officials were spotted using the slurs.
TNW Conference 2024, June 20-21 – Exclusive Group Promotion – Ends March 29!
The ultimate team-building experience: Buy 2, get 1 FREE – Buy 3-4, get 2 FREE – Buy 5+, get 3 FREE!
Osavul said the vocabulary deliberately conceals the racial and ethnic undertones from foreign eyes.
“Russian slang helps to hide negative attitudes towards national minorities and immigrants inside Russia and gets hatred towards them in society,” Andrew Bevz, the startup’s chief marketing officer, told TNW.
The most widespread barb was “foreign specialist” (инностранный специалист). Used ironically, the term ridicules the qualifications and education levels of migrants.
Osavul also unearthed curious correlations between the slurs and current events.
Hidden in plain sight on Russian media
Neighbouring states were frequent targets of the insults. According to Osavul’s research, Russian neo-imperial discourse often depicts these nations as rebellious provinces and traitors.
A common example is using the phrase “on Ukraine” instead of “in Ukraine,” which implies the country is not truly independent.
Poland was also repeatedly denigrated. The AI system regularly detected the pejorative “psheks,” a Russian slur that imitates a common sound in spoken Polish.
The word’s prevalence aligned with political developments. Usage peaked after former Russian president Dmitry Medvedev posted the word on Telegram last August. It then spread across the internet.
Sightings of the term declined when Poland blockaded Ukrainian grain imports in September. Negativity towards Poles in Russian online spaces subsequently decreased.
Another emergent “dog whistle” is the use of “Abramovichs,” (Абрамовичи) “Galkins,” (Галкины) and “Chubaises” (Чубайсы).
All three words are taken from the surnames of prominent Russian Jews. By pluralising them, users equate Jewish origins with opposition to Russia.
Osavul also discovered mockery of the Soviet ideology of “friendship of nations.” Across online media, the term “multinational” (многнационал) and its derivates have now harnessed to criticise diversity.
These findings showcase AI’s potential to analyse online language. Bevz argues that they also expose a national trend.
“Russian society no longer believes in the ‘multicultural’ discourse inherited from the USSR and sold by the current government in the global arena,” he said.
One of the themes of this year’s TNW Conference is Ren-AI-ssance: The AI-Powered Rebirth. If you want to go deeper into all things artificial intelligence, or simply experience the event (and say hi to our editorial team), we’ve got something special for our loyal readers. Use the code TNWXMEDIA at checkout to get 30% off your business pass, investor pass
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