This work outlines how we prioritize original news, a critical indicator of news quality. By examining the landscape and life-cycle of news posts on our social media platform, we identify challenges of building and deploying an originality score. We pursue an approach based on normalized PageRank values and three-step clustering, and refresh the score on an hourly basis to capture the dynamics of online news. We describe a near real-time system architecture, evaluate our methodology, and deploy it to production. Our empirical results validate individual components and show that prioritizing original news increases user engagement with news and improves proprietary cumulative metrics.

中文翻译：

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在Facebook上优先处理原始新闻

这项工作概述了我们如何优先处理原始新闻，这是新闻质量的关键指标。通过在我们的社交媒体平台上检查新闻发布的格局和生命周期，我们确定了构建和部署创意评分的挑战。我们采用基于归一化PageRank值和三步聚类的方法，并每小时刷新一次分数以捕获在线新闻的动态。我们描述了一种近乎实时的系统架构，评估了我们的方法，并将其部署到生产中。我们的经验结果验证了各个组成部分，并显示了对原始新闻进行优先级排序可以增加用户对新闻的参与度并改善专有的累积指标。