structural:scholar_edition
Algorithm

On October 21, 2021, a report based on a "long-running, massive-scale randomized experiment" that analyzed "millions of tweets sent between 1 April and 15 August 2020", found that Twitter's machine learning recommendation algorithm amplified right-leaning politics on personalized user Home timelines.: 1 The report compared seven countries with active Twitter users where data was available (Germany, Canada, the United Kingdom, Japan, France, and Spain) and examined tweets "from major political groups and politicians".: 4 Researchers used the 2019 Chapel Hill Expert Survey (CHESDATA) to position parties on political ideology within each country.: 4 The "machine learning algorithms", introduced by Twitter in 2016, personalized 99% of users' feeds by displaying tweets (even older tweets and retweets from accounts the user had not directly followed) that the algorithm had "deemed relevant" to the users' past preferences.: 4 Twitter randomly chose 1% of users whose Home timelines displayed content in reverse-chronological order from users they directly followed.: 2