论文标题
统一数据观点和个性化：社会规范的应用
Unifying Data Perspectivism and Personalization: An Application to Social Norms
论文作者
论文摘要
最近的一些研究没有将单个基础真理用于语言处理任务，而是研究了如何表示和预测注释者集的标签。但是，通常很少或没有关于注释者的信息，或者一组注释者很小。在这项工作中，我们研究了一系列社交媒体文章，内容涉及一组13K注释者和21万个社会规范的判断。我们提供了一种新颖的实验设置，该设置将个性化方法应用于注释者的建模，并比较其预测社会规范感知的有效性。我们进一步提供了社会情况下的绩效的分析，这些绩效因冲突中当事方之间关系的亲密关系而异，并评估个性化最大的帮助。
Instead of using a single ground truth for language processing tasks, several recent studies have examined how to represent and predict the labels of the set of annotators. However, often little or no information about annotators is known, or the set of annotators is small. In this work, we examine a corpus of social media posts about conflict from a set of 13k annotators and 210k judgements of social norms. We provide a novel experimental setup that applies personalization methods to the modeling of annotators and compare their effectiveness for predicting the perception of social norms. We further provide an analysis of performance across subsets of social situations that vary by the closeness of the relationship between parties in conflict, and assess where personalization helps the most.
