Twitter finds its algorithms amplify the political right

The first part of an internal study examined tweets from elected officials and news outlets in seven countries including Canada, France, Germany, Japan, Spain, the United Kingdom, and the United States.

Twitter has found that tweets posted by accounts from political rights receive more algorithmic amplification than the political left.

(Sign up to our Technology newsletter, Today's Cache, for insights on emerging themes at the intersection of technology, business and policy. Click here to subscribe for free.)

The first part of an internal study examined tweets from elected officials and news outlets in seven countries including Canada, France, Germany, Japan, Spain, the United Kingdom, and the United States.

The social media platform found apparent bias in six out of seven countries, except Germany, when studied as a group.

Right-leaning news outlets saw greater algorithmic amplification on Twitter compared to left-leaning news outlets. Besides, the findings revealed that group effects did not translate to individual effects as party affiliation or ideology is not a factor when recommending content, meaning, two individuals in the same political party would not necessarily see the same amplification.

“Tweets about political content from elected officials, regardless of party or whether the party is in power, do see algorithmic amplification when compared to political content on the reverse-chronological timeline,” Twitter said in a blog post.

However, the microblogging site could not establish why the algorithm leaned towards the right, according to Rumman Chowdhury, Director, Software Engineering at Twitter.

Twitter’s algorithms are responsive to what’s happening and the company will examine to find out the root cause of the bias, Chowdhury added.

For the study, Twitter analysed millions of Tweets from April 1 to August 15, 2020, from accounts operated by elected officials in seven countries. The company explained It used the data to test whether or not these Tweets are amplified more on the algorithmically ranked Home timeline than the reverse-chronological feed and whether there was variance within a party.

For news outlets, Twitter analysed tweets containing links to articles shared by people on the platform during the same time period.