论文标题
非人性化计算语言分析的框架
A Framework for the Computational Linguistic Analysis of Dehumanization
论文作者
论文摘要
非人性化是一个有害的心理过程，通常会导致针对目标社会群体的极端群体间偏见，仇恨言论和暴力。尽管这些严重的后果和可用的数据丰富，但尚未大规模研究非人性化。通过社会心理学研究，我们创建了一个计算语言框架，用于通过识别非人性化显着组成部分的语言相关性来分析非人性化语言。然后，我们将此框架应用于1986年至2015年《纽约时报》中LGBTQ人的讨论。总体而言，随着时间的推移，我们发现对LGBTQ人的描述越来越多。但是，我们发现同性恋的标签与其他标签（例如同性恋）相比，与非人性化态度相关。我们提出的技术突出了语言变化和边缘化群体周围的话语的变化过程。此外，大规模分析非人性化语言的能力对自动检测和理解媒体偏见以及在线滥用语言具有影响。
Dehumanization is a pernicious psychological process that often leads to extreme intergroup bias, hate speech, and violence aimed at targeted social groups. Despite these serious consequences and the wealth of available data, dehumanization has not yet been computationally studied on a large scale. Drawing upon social psychology research, we create a computational linguistic framework for analyzing dehumanizing language by identifying linguistic correlates of salient components of dehumanization. We then apply this framework to analyze discussions of LGBTQ people in the New York Times from 1986 to 2015. Overall, we find increasingly humanizing descriptions of LGBTQ people over time. However, we find that the label homosexual has emerged to be much more strongly associated with dehumanizing attitudes than other labels, such as gay. Our proposed techniques highlight processes of linguistic variation and change in discourses surrounding marginalized groups. Furthermore, the ability to analyze dehumanizing language at a large scale has implications for automatically detecting and understanding media bias as well as abusive language online.
