Study suggests Twitter algorithm amplifies conservatives, not liberals


Democrats and Republicans in Congress demonstrated a rare moment of bipartisan unity just weeks before the 2020 presidential election. The House Judiciary Committee was holding a hearing on whether big tech companies like Facebook and Twitter should be dismantled. While many witnesses discussed antitrust law and other regulatory matters, Rep. Jim Jordan (R-Ohio) made it clear that he has a whole different agenda.

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Jordan said, “Big Tech is trying to get Tories.” “It’s not a rumor. This is not a wild guess. This is a proven fact. This is something I said at our last hearing two months ago. It is still true today. However, Jordan’s so-called ‘fact’ appears to be far from the truth, according to a new study. Users of the algorithm are forced to work with conservative and non-liberal media voices, at least when it comes to a large social media network.

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The authors of “Algorithmic Amplification of Politics on Twitter,” which was published in the journal Proceedings of the National Academy of Sciences (PNAS), say they conducted a “large-scale experiment involving millions of Twitter users, a detailed analysis of political parties in seven countries and 6.2 million press articles shared in the United States. A member of Twitter’s machine learning ethics, transparency and accountability team co-authored the work with researchers from the University of Cambridge, University College London and the University of California to Berkeley.

The results are divided into two categories. One section, which focused on the United States, examined whether mainstream media with strong political leanings were more likely to be amplified by Twitter’s algorithm. (It doesn’t matter your philosophy.) The other section of the study examined tweets from seven different countries, focusing on those posted by elected leaders of major political parties. Despite fears that extremists will disproportionately profit from algorithms on social media platforms, researchers have found no indication that Twitter’s algorithm amplifies extremist views more than traditional views. They did, however, see a telling pattern in how the different types of media material performed on the platform.

“Our results reveal a surprisingly consistent trend: the dominant political right enjoys higher algorithmic amplification than the dominant political left in six of the seven countries analyzed,” the authors write. “Our second set of results, which examined the US media environment, indicated that algorithmic amplification favors right-wing news sources, which is consistent with the general trend.”


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