根据参与和不参与的信号进行排名:从行业学习
Tom Cunningham1, Sana Pandey2, Leif Sigerson3
1OpenAI Inc, San Francisco, California, USA.
Annals of the New York Academy of Sciences
|August 21, 2025
概括
通过与参与度指标一起使用非参与度信号,平台可以提高用户保留率和社会效益. 这项研究建议整合用户调查和质量指标以提高在线内容的排名.
科学领域:
- 数字媒体
- 人与计算机的交互
- 社会影响
背景情况:
- 在线平台通常优先考虑用户参与内容排名.
- 这种关注可能会忽视平台和社会福祉的其他有价值的指标.
- 没有参与的信号有可能改善平台的结果.
研究的目的:
- 探索在线媒体平台中的不参与信号的潜力.
- 制定基于共识的关于整合不参与信号的建议.
- 检查参与,不参与信号和用户保留之间的关系.
主要方法:
- 召开了一个与行业和学术专家的研讨会.
- 通过专家的共识制定建议.
- 用公开可用的证据和定量数据支持提案.
主要成果:
- 制定了关于非参与信号的作用和影响的建议.
- 显示了非参与信号与用户保留之间的潜在联系.
- 提供了支持整合不同排名因素的证据.
结论:
- 整合非参与信号可以提高平台价值和社会效益.
- 专家的共识支持内容排名的更广泛的方法.
- 分享这些见解有助于在线平台的设计和评估.
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