Twitter claims not to know what causes the amplification.
Twitter is publicly sharing research findings today that show that the platform’s algorithms amplify tweets from right-wing politicians and content from right-leaning news outlets more than people and content from the political left.
The research did not identify whether or not the algorithms that run Twitter’s Home feed are actually biased toward conservative political content, because the conclusions only show bias in amplification, not what caused it. Rumman Chowdhury, the head of Twitter’s machine learning, ethics, transparency and accountability team, called it “the what, not the why” in an interview with Protocol.
“We can see that it is happening. We are not entirely sure why it is happening. To be clear, some of it could be user-driven, people’s actions on the platform, we are not sure what it is. It’s just important that we share this information,” Chowdhury said. The META team plans to conduct what she called a “root-cause analysis” to try to discover the “why,” and that analysis will likely include creating testable hypotheses about how people use the platform that could help show whether it’s the way users interact with Twitter or the algorithm itself that is causing this uneven amplification.
It’s great to see Twitter releasing research that is potentially damaging, and not try to bury it. Speaks to credibility. Shows they are working on important issues, learning, and trying to be better.
Today, we’re publishing learnings from another study: an in-depth analysis of whether our recommendation algorithms amplify political content. The first part of the study examines Tweets from elected officials* in seven countries (Canada, France, Germany, Japan, Spain, the United Kingdom, and the United States). Since Tweets from elected officials cover just a small portion of political content on the platform, we also studied whether our recommendation algorithms amplify political content from news outlets.
What did we find?
- 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.
- Group effects did not translate to individual effects. In other words, since party affiliation or ideology is not a factor our systems consider when recommending content, two individuals in the same political party would not necessarily see the same amplification.
- 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.
- Right-leaning news outlets, as defined by the independent organizations listed above, see greater algorithmic amplification on Twitter compared to left-leaning news outlets. However, as highlighted in the paper, these third-party ratings make their own, independent classifications and as such the results of analysis may vary depending on which source is used.