论文标题
毒性检测：上下文真的重要吗？
Toxicity Detection: Does Context Really Matter?
论文作者
论文摘要
适度对于促进健康的在线讨论至关重要。尽管已经发布了几个“毒性”检测数据集和模型，但其中大多数忽略了帖子的上下文，隐含地假设评论可能是独立判断的。我们通过关注两个问题来调查这一假设：（a）上下文是否会影响人类的判断，（b）在上下文上的条件是否可以改善毒性检测系统的性能？我们尝试Wikipedia对话，将上下文的概念限制在主题和讨论标题中的上一篇文章中。我们发现，上下文可以放大或减轻帖子的毒性。此外，如果没有提供注释者，则一小部分但重要的手动标记帖子（在我们的一个实验中为5％）最终具有相反的毒性标签。令人惊讶的是，我们还没有发现上下文实际上改善了毒性分类器的性能，但尝试了一系列分类器和机制来使它们意识到上下文。这表明需要在上下文中注释的大型注释数据集。我们公开提供代码和数据。
Moderation is crucial to promoting healthy on-line discussions. Although several `toxicity' detection datasets and models have been published, most of them ignore the context of the posts, implicitly assuming that comments maybe judged independently. We investigate this assumption by focusing on two questions: (a) does context affect the human judgement, and (b) does conditioning on context improve performance of toxicity detection systems? We experiment with Wikipedia conversations, limiting the notion of context to the previous post in the thread and the discussion title. We find that context can both amplify or mitigate the perceived toxicity of posts. Moreover, a small but significant subset of manually labeled posts (5% in one of our experiments) end up having the opposite toxicity labels if the annotators are not provided with context. Surprisingly, we also find no evidence that context actually improves the performance of toxicity classifiers, having tried a range of classifiers and mechanisms to make them context aware. This points to the need for larger datasets of comments annotated in context. We make our code and data publicly available.
