An internal study published by Twitter on its algorithms indicated that the platform actually amplifies right-of-center voices over left-leaning ones.
The reality, however, is more complicated.
Rumman Chowdhury, the head of Twitter's machine learning, ethics, transparency and accountability (META) team, told Protocol that the study only showed results based on bias in amplification–not what caused it. The content could be amplified for any reason.
In short, the study was unable to determine whether Twitter’s home feed algorithms are biased towards conservative content. Interestingly, Twitter did not specify which outlets or politicians are considered “right-wing” by the platform.
"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.
She added that the META team will conduct a "root-cause analysis” to discover why the purported skew exists, including analyzing how users interact with the platform’s algorithms.
Chowdhury said that Twitter has yet to discover why certain content gets amplified. "When algorithms get put out into the world, what happens when people interact with it, we can't model for that. We can't model for how individuals or groups of people will use Twitter, what will happen in the world in a way that will impact how people use Twitter," she said.
She also argued that the problem is not solely a Twitter issue, implying that other social media platforms are struggling with algorithm data as well. "Anybody who makes algorithms and relies on them has the same questions we have," she concluded.
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