Pinterest如何利用机器学习为健康的评论生态系统提供动力

Yuanfang Song | Machine Learning Engineer, Trust and Safety; Qinglong Zeng | Engineering Manager, Content Quality Signals; and Vishwakarma Singh | Machine Learning Lead, Trust and Safety

宋远方|机器学习工程师,信任与安全;曾庆龙|工程经理,内容质量信号;以及Vishwakarma Singh|机器学习负责人,信任与安全

As Pinterest continues to evolve from a place to just save ideas to a platform for discovering content that inspires action, there’s been an increase in native content from creators publishing directly to Pinterest. With the creator ecosystem on Pinterest growing, we’re committed to ensuring Pinterest remains a positive and inspiring environment through initiatives like the Creator Code, a content policy that enforces the acceptance of guidelines (such as “be kind” and “check facts”) before creators can publish Idea Pins. We also have guardrails in place on Idea Pin comments including positivity reminders, tools for comment removal and keyword filtering, and spam prevention signals. On the technical side, we use cutting edge techniques in machine learning to identify and enforce against community policy-violating comments in near real-time. We also use these techniques to surface the most inspiring and highest quality comments first in order to bring a more productive experience and drive engagement.

随着Pinterest不断发展,从一个只是保存想法的地方发展到一个发现激发行动的内容的平台,创作者直接发布到Pinterest的原生内容越来越多。随着Pinterest上创作者生态系统的增长,我们致力于通过创作者守则等举措确保Pinterest保持一个积极和鼓舞人心的环境,这是一项内容政策,在创作者发布创意图钉之前强制接受一些准则(如 "要有爱心 "和 "检查事实")。我们还为创意图钉的评论设置了护栏,包括积极性提醒、评论删除和关键词过滤工具,以及垃圾邮件预防信号。在技术方面,我们使用机器学习的尖端技术,以近乎实时的方式识别和执行违反社区政策的评论。我们还使用这些技术,首先浮现出最有启发性和最高质量的评论,以带来更多的经验和推动参与。

Since machine learning solutions were introduced in March to automatically detect potentially policy-violating comments before they’re reported and take appropriate action, we’ve seen a 53% decline in comment report rates (user comment reports per 1 million comment impressions).

自从3月份引入机器学习解决方案,在报告之前自动检测可能违反政策的评论并采取适当的行动以来,我们看到评论报告率(每100万条评论的用户评论报告)下降了53%。

Here, we share how we built a scalable near-real time machine learning solution to identify poli...

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