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.

本研究根据社会心理学的研究，创建了一个计算语言分析框架来分析去人性化言论，然后将这个框架应用于分析New York Times自1986年至2015年关于LGBTQ人士的文章。总体而言，我们发现随着时间的推移，LGBTQ人士的被人性化描述越来越多。但是，我们发现与其他标签（例如同性恋）相比，“同性恋”这个标签更容易被视为去人性化的态度。本文所提出的技术揭示了围绕边缘化群体的语言变化和变异的过程，并且大规模分析非人性化言论的能力对于自动检测和理解媒体偏见以及虐待性言论的意义重大。

计算语言学分析的去人化框架