论文标题
在信息共享平台上刻度content-mododeration-scale的轮毂和辐条模型
A Hub-and-Spoke Model for Content-Moderation-at-Scale on an Information-Sharing Platform
论文作者
论文摘要
维护现代信息共享平台（例如，网络搜索，社交网络）的最昂贵部分之一是内容 - 调整范围的任务。内容审核是确定给定用户创建的消息是否符合编辑团队的网站内容准则的二进制任务。挑战在于，用用户数量检查量表的消息数量比为给定平台工作的主持人雇员数量要大得多。 我们通过有效地平台化内容审核的任务来展示如何比以前更便宜地实现内容审核。我们的方法是使用轮毂和辐条模型。枢纽是由给定平台管理层委派的核心编辑团队。辐条是个体用户。编辑团队的评分为统计学习算法创建标签，而用户的评分被用作功能。 我们已经在“ thinkDifferentagain.art”的开源尺寸尺寸库中实现了该算法的原始版本。
One of the most expensive parts of maintaining a modern information-sharing platform (e.g., web search, social network) is the task of content-moderation-at-scale. Content moderation is the binary task of determining whether or not a given user-created message meets the editorial team's content guidelines for the site. The challenge is that the number of messages to check scales with the number of users, which is much larger than the number of moderator-employees working for the given platform. We show how content moderation can be achieved significantly more cheaply than before, in the special case where all messages are public, by effectively platformizing the task of content moderation. Our approach is to use a hub-and-spoke model. The hub is the core editorial team delegated by the management of the given platform. The spokes are the individual users. The ratings of the editorial team create the labels for a statistical learning algorithm, while the ratings of the users are used as features. We have implemented a primitive version of this algorithm into our open-source DimensionRank code base, found at "thinkdifferentagain.art".
