对推特推系统的众包审计
Paul Bouchaud1,2, David Chavalarias3,4, Maziyar Panahi3
1CNRS, Complex Systems Institute of Paris Île-de-France (ISC-PIF), 75013, Paris, France. paul.bouchaud@iscpif.fr.
Scientific reports
|October 5, 2023
概括
这项研究对Twitter的推系统进行了审计,发现它可以放大来自同一个社区的朋友和充满情感的内容. 算法策划显示不均的政治倾向放大,突出了需要透明度.
科学领域:
- 社交媒体分析 社交媒体分析
- 算法审计是一种算法审计.
- 计算社会科学 计算社会科学
背景情况:
- 社交媒体平台利用推系统来策划用户内容.
- 了解算法对用户体验和信息曝光的影响至关重要.
研究的目的:
- 对Twitter的推系统进行审计,以查看用户订阅和时间线内容之间的差异.
- 调查算法放大模式及其潜在偏差.
主要方法:
- 使用浏览器扩展用于数据收集.
- 使用Twitter API进行全面的数据检索.
- 对推者系统的输出进行了审计.
主要成果:
- 观察到来自同一社区的用户的内容显著放大.
- 确定了对放大充满情感和有毒推文的偏好.
- 在用户朋友的政治倾向中检测到不均的算法放大.
结论:
- 推特的算法在内容放大方面表现出偏见.
- 算法策划显著影响用户信息曝光.
- 提高透明度和对推者系统影响的认识是必不可少的.
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