Social media platforms attempting to curb abuse and misinformation have been accused of political bias. We deploy neutral social bots on Twitter to probe biases that may emerge from interactions between users, platform mechanisms , and manipulation by inauthentic actors . We find evidence of bias affecting the news and information to which U.S. Twitter users are likely to be exposed , depending on their own political alignment . Partisan accounts, especially conservative ones, tend to receive more followers,  follow more automated accounts , and find themselves in echo chambers . Conservative accounts are  exposed to more low-credibility content . Liberal accounts are exposed to moderate content shifting their experience toward the political center, while the interactions of conservative accounts are skewed toward the right. We find some evidence of central bias in the news feed ranking algorithm for partisan accounts. These findings help inform the public debate about how social media shape exposure to political information .
Social media platforms attempting to curb abuse and misinformation have been accused of political bias. We deploy neutral social bots who start following different news sources on Twitter, and track them to probe distinct biases emerging from platform mechanisms versus user interactions . We find no strong or consistent evidence of political bias in the news feed. Despite this, the news and information to which U.S. Twitter users are exposed depend strongly on the political leaning of their early connections. The interactions of conservative accounts are skewed toward the right, whereas liberal accounts are exposed to moderate content shifting their experience toward the political center . Partisan accounts, especially conservative ones, tend to receive more followers, find themselves in denser communities, and follow more automated accounts . Conservative accounts are also exposed to more low-credibility content .
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on Twitter to probe biases that may emerge from interactions between users, platform mechanisms , and manipulation by inauthentic actors
who start following different news sources on Twitter, and track them to probe distinct biases emerging from platform mechanisms versus user interactions
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evidence of bias affecting the news
no strong or consistent evidence of political bias in the news feed. Despite this, the news
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likely to be exposed , depending on their own political alignment
exposed depend strongly on the political leaning of their early connections. The interactions of conservative accounts are skewed toward the right, whereas liberal accounts are exposed to moderate content shifting their experience toward the political center
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find themselves in denser communities, and
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, and find themselves in echo chambers
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also
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. Liberal accounts are exposed to moderate content shifting their experience toward the political center, while the interactions of conservative accounts are skewed toward the right. We find some evidence of central bias in the news feed ranking algorithm for partisan accounts. These findings help inform the public debate about how social media shape exposure to political information