Twitter says its algorithm is biased toward RIGHT-WING content, says it will study results of ‘problematic’ review
Twitter has said that its algorithms amplify content from right-wing politicians and news outlets more than others but it does not know why. The platform described the findings, by a recent internal review, as “problematic.”
The study analyzed millions of tweets posted by elected officials in seven countries – Canada, France, Germany, Japan, Spain, the UK, and the US – between April and mid-August 2020. It found that, with the exception of Germany, content posted by the political right received more exposure on the platform than left-wing political entities’ content.
The internal review also examined hundreds of millions of tweets with links to content from news outlets during the same period – but not tweets directly shared by the primarily US media groups themselves. This revealed that conservative news portals benefited from greater algorithmic amplification as well.
Twitter noted that it didn’t categorize news outlets as left-leaning or right-leaning itself, but relied on classifications from “independently curated” third parties.
The study conducted a comparison of the platform’s ‘Home’ timeline, where it says its 200 million users see algorithm-tailored tweets based on their preferences, with a chronological timeline, where only the most recent posts were shown first. One finding was that politicians’ tweets were generally more amplified by the algorithmic timeline, particularly right-wing politicians.
In a blog post on Thursday, Rumman Chowdhury, Twitter’s software engineering director, and Luca Belli, a machine learning researcher, termed the findings “problematic” and indicated that changes might be required to “reduce adverse impacts” of the Home timeline algorithm.
“Algorithmic amplification is problematic if there is preferential treatment as a function of how the algorithm is constructed versus the interactions people have with it,” the post said, noting that the company needed “further root cause analysis” to explain why there was a bias in amplification.
The study conducted a comparison of the platform’s ‘Home’ timeline, where it says its 200 million users see algorithm-tailored tweets based on their preferences, with a chronological timeline, where only the most recent posts were shown first. One finding was that politicians’ tweets were generally more amplified by the algorithmic timeline, particularly right-wing politicians.
In a blog post on Thursday, Rumman Chowdhury, Twitter’s software engineering director, and Luca Belli, a machine learning researcher, termed the findings “problematic” and indicated that changes might be required to “reduce adverse impacts” of the Home timeline algorithm.
“Algorithmic amplification is problematic if there is preferential treatment as a function of how the algorithm is constructed versus the interactions people have with it,” the post said, noting that the company needed “further root cause analysis” to explain why there was a bias in amplification.
https://www.rt.com/usa/538230-twitter-algorithm-bias-right-wing/