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The political effects of X's feed algorithm.

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Area of Science:

  • Social Sciences
  • Computational Social Science
  • Political Science

Background:

  • Social media algorithms are suspected to influence political attitudes.
  • Previous research on Meta platforms showed no political effects from algorithm changes.
  • The impact of algorithms on political attitudes remains a key research question.

Purpose of the Study:

  • To investigate the political effects of algorithmic content curation on the social media platform X.
  • To compare the effects of algorithmic versus chronological feeds on user attitudes and behavior.
  • To identify the mechanisms driving any observed political effects.

Main Methods:

  • A field experiment was conducted on X with active US users over 7 weeks.
  • Users were randomly assigned to either an algorithmic or a chronological feed.
  • Political attitudes, online behavior, feed content, and user engagement were measured.

Main Results:

  • Switching to an algorithmic feed increased engagement and shifted political opinions towards conservative stances.
  • Algorithmic feeds promoted conservative content and demoted traditional media posts.
  • Users exposed to the algorithm followed conservative accounts, showing persistent behavioral changes.

Conclusions:

  • Initial exposure to X's algorithm has persistent effects on political attitudes and following behavior.
  • The algorithm's promotion of conservative content and activist accounts explains the observed effects.
  • Unlike previous findings, this study demonstrates a significant political impact of social media feed algorithms.