Twitter’s algorithm favors right-wing politics, according to research

Twitter amplifies tweets from political parties and media outlets on the right rather than the left, its own research suggests.

The social media giant said it made the discovery while exploring how its algorithm recommends political content to users.

But he admitted he didn’t know why, saying it was a “harder question to answer”.

Twitter has already faced claims of anti-conservative bias on its platform.

The Twitter study looked at tweets from political parties and users sharing content from news agencies in seven countries around the world: Canada, France, Germany, Japan, Spain, the United Kingdom and the United States.

It analyzed millions of tweets sent between April 1 and August 15, 2020.

The researchers then used the data to see which tweets were amplified more on an algorithmically sorted feed than on a reverse chronological feed, both of which users have the ability to use.

They have found that major right-wing parties and media outlets enjoyed higher levels of “algorithmic amplification” than their left-wing counterparts.

Rumman Chowdhury, director of Twitter’s Meta (machine learning, ethics, transparency and accountability) team, said the company’s next step was to uncover the reason behind the phenomenon.

“In six out of seven countries, tweets posted by elected officials on the political right are algorithmically amplified more than the political left. News on the right … see more amplification than those on the left,” he said.

“Establishing why these observed patterns occur is a much more difficult question to answer and something Meta will look into.”

The researchers noted that the difference in amplification could be due to the “different strategies” used by political parties to reach audiences on the platform.

They also said the findings do not suggest that its algorithms push “extreme ideologies more than traditional political voices” – another common concern voiced by Twitter critics.

This isn’t the first time Twitter has highlighted an apparent bias in its algorithm.

In April, the platform revealed that it was conducting a study to determine whether its algorithms contributed to “unintended damage”.

In May, the company revealed that automatic image cropping had underlying issues that favored whites over blacks and women over men.