Twitter algorithm amplifies right-wing voices, study findsVish Gainon January 5, 2022 at 11:29 Silicon RepublicSilicon Republic


It’s been almost exactly a year since the 6 January riots at the US Capitol Building that shocked the world and highlighted the potential dangers of unregulated content on social media.

And now, a global team of researchers has found that Twitter’s algorithm that decides what users see on their feed disproportionately favours right wing politicians over left-wing ones.

Twitter uses an algorithm to personalise the content seen by users on their home timelines. Politicians on both sides of the political spectrum often allege that their opponents’ voices get more amplification on social media – a claim that is often hard to verify.

Ferenc Huszár of Cambridge University, along with a team of researchers on both sides of the Atlantic, conducted a large-scale study involving a randomised control group of nearly 2m daily active Twitter users. This group received content from Twitter in reverse chronological order without personalisation.

Alongside this group, the team also studied a separate treatment group representing 4pc of all other accounts with personalised timelines.

Using these two groups, the team analysed the algorithmic amplification effect on tweets from 3,634 elected politicians from major political parties in seven countries that are highly represented on Twitter. They also measured the algorithmic amplification of 6.2m political news articles shared on Twitter in the US.

Based on these analyses, the team found that in six of the seven countries, the mainstream political right enjoyed significantly higher levels of amplification over the mainstream political left – indicating a clear bias in the algorithm.

However, contrary to popular belief, there was no evidence to prove that the algorithm amplified far-right and far-left political groups over more moderate ones.

The study was published yesterday (4 January) in the Proceedings of the National Academy of Sciences of the United States of America, or PNAS. Huszár, who is a senior lecturer of machine learning at Cambridge, led a team of researchers including Sofia Ira Ktena, Conor O’Brien, Luca Belli, Andrew Schlaikjer and Moritz Hardt.

“This study carries out the most comprehensive audit of an algorithmic recommender system and its effects on political content,” the study read. “We hope our findings will contribute to an evidence-based debate on the role personalization algorithms play in shaping political content consumption.”

In an editorial accompanying the article, Susan Fiske, a social psychologist at Princeton University, wrote that the findings raise ethical questions about Twitter’s impact on our democracies.

“On the lofty assessment of Twitter’s corporate responsibility, this article will prompt much debate. Holiday dinners just got more interesting,” she wrote.

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