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An anonymous reader quotes a report from The Conversation: Twitter has on various occasions been accused of political bias, with politicians or commentators alleging Twitter's algorithm amplifies their opponents' voices, or silences their own. In this climate, Twitter commissioned a study to understand whether their algorithm may be biased towards a certain political ideology. While Twitter publicized the findings of the research in 2021, the study has now been published in the peer-reviewed journal PNAS. The study looked at a sample of 4% of all Twitter users who had been exposed to the algorithm (46,470,596 unique users). It also included a control group of 11,617,373 users who had never received any automatically recommended tweets in their feeds. This wasn't a manual study, whereby, say, the researchers recruited volunteers and asked them questions about their experiences. It wouldn't 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 found that in six out of the seven countries (Germany was the exception), the algorithm significantly favored the amplification of tweets from politically right-leaning sources. Overall, the amplification trend wasn't significant among individual politicians from specific parties, but was when they were taken together as a group. The starkest contrasts were seen in Canada (the Liberals' tweets were amplified 43%, versus those of the Conservatives at 167%) and the UK (Labour's tweets were amplified 112%, while the Conservatives' were amplified at 176%). In acknowledgement of the fact that tweets from elected officials represent only a small portion of political content on Twitter, the researchers also looked at whether the algorithm disproportionately amplifies news content from any particular point on the ideological spectrum. 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. Similar to the results in the first part of the study, the authors found that content from right-wing media outlets is amplified more than that from outlets at other points on the ideological spectrum. This part of the study also found far-left-leaning and far-right-leaning outlets were not significantly amplified compared with politically moderate outlets. The authors of the study point out that the algorithms "might be influenced by the way different political groups operate," notes The Conversation. "So for example, some political groups might be deploying better tactics and strategies to amplify their content on Twitter."