Twitter’s algorithm amplifies right-leaning political content and news outlets more than left-leaning content, the social media giant said on Thursday, citing a research study it recently conducted.

Twitter, however, said that establishing why this takes place is significantly more difficult, as it is “a product of the interactions between people and the platform”.

The research examined tweets from elected officials in seven countries – Canada, France, Germany, Japan, Spain, the United Kingdom and the United States.

The study was conducted from April 1 to August 15 last year. Researchers studied which tweets were amplified more on algorithmically-ordered feeds as compared to reverse-chronological feeds.

Since 2016, Twitter users have had the option to choose between the two kinds of feeds. Algorithmically-ordered feeds show tweets from accounts that a user follows, and also other tweets that the user is likely to be interested in based on their past activity. In a reverse-chronological feed, a user sees most recent tweets first.

“In six out of seven countries – all but Germany – tweets posted by accounts from the political right receive more algorithmic amplification than the political left when studied as a group,” the study concluded.

The study also showed that Twitter’s algorithms amplified right-leaning media outlets more than left-leaning ones. It said that two independent organisations, AllSides and Ad Fontes Media, categorised news outlets as left-leaning or right-leaning.

“Our analysis of far-left and far-right parties in various countries does not support the hypothesis that algorithmic personalisation amplifies extreme ideologies more than mainstream political voices.,” the study added. “However, some findings point at the possibility that strong partisan bias in news reporting is associated with higher amplification.”

Ferenc Huszár, one of the authors of the study, told the Hindustan Times that there could be many reasons why Twitter’s algorithms amplify right-leaning content more.

“Differences may arise, for example, from people with different political interests simply using Twitter differently: some communities might use the retweet, like or reply functions more, or attach a slightly different relevance to each of these actions,” he said.