In other words, Twitter is recommending content to you that it deems may appeal to you.
WhileTwitterpublicized the findings of the research in 2021, thestudyhas now been published in the peer-reviewed journal PNAS.
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It wouldnt have been possible to study such a large number of users that way.
Instead, a computer model allowed the researchers to generate their findings.
The researchers computed amplification based on counting events called linger impressions.
To this end, they measured the algorithmic amplification of 6.2 million political news articles shared in the US.
To determine the political leaning of the news source, they used two independently curated media bias-rating datasets.
As the authors point out, the algorithms might be influenced by the way different political groups operate.
It is pleasing to seeTwittertaking the initiative to carry out this kind of research, and reviewing the findings.
