Twitter published an internal analysis on their algorithms that showed the platform amplifies left-leaning voices more than right-ofcenter ones.
Reality is, however, more complicated
Rumman Chowdhury is the Twitter machine learning, ethics and transparency (META), team leader. Protocol that the study only showed results based on bias in amplification–not what caused it. Any reason could have an effect on the content.
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.
It is obvious that this is taking place. It is not clear why. We aren’t sure why it happens. Some of it may be user-driven. Chowdhury stated that it was important to share the information.
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 claimed that Twitter still has not discovered why certain content is amplified. Chowdhury stated that algorithms can be released to the public, but we cannot model what people do with them. “We can’t predict the behavior of individuals and groups using Twitter or how it will affect how they use Twitter,” she stated.
Also, she said that this problem is not just Twitter’s. It implies that algorithms data are being hampered by other social media platforms. She concluded that “anyone who creates algorithms and depends on them has the exact same questions as us.”
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