Twitter admits its algorithm disproportionately amplifies right wing political content

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Twitter admits its algorithm disproportionately amplifies right wing political content



Twitter’s own research has found that its algorithm disproportionately amplifies right wing political content and news sources in an analysis involving millions of its users across seven countries. The social media company’s researchers are unsure why that is happening. India was not among the seven countries studied.The social media platform examined tweets from elected officials in seven countries – the UK, US, Canada, France, Germany, Spain and Japan. According to a 27-page document, Twitter found a “statistically significant difference favouring the political right wing” in all the countries except Germany. Under the research, a value of 0% meant tweets reached the same number of users on the algorithm-tailored timeline as on its chronological counterpart, whereas a value of 100% meant tweets achieved double the reach.Twitter’s new study co-authored by six researchers and released by the company this week, found that its algorithm amplifies right wing political narratives. “Our results reveal a remarkably consistent trend: In 6 out of 7 countries studied, the mainstream political right enjoys higher algorithmic amplification than the mainstream political left. Consistent with this overall trend, our second set of findings studying the US media landscape revealed that algorithmic amplification favours right-leaning news sources,” said the study, involving academics from University of Cambridge, UC Berkley and University College London. The study looked at millions of tweets from politicians across seven countries and hundreds of millions of tweets of links from news outlets, not tweets from the outlets themselves.In a series of tweets detailing the findings, Twitter’s director of software engineering Rumman Chowdhury, said “Twitter is a sociotechnical system — our algos are responsive to what’s happening. What’s next is a root cause analysis — is this unintended model bias? Or is this a function of what and how people tweet, and things that are happening in the world? Or both?” the Twitter staffer added in another tweet.



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