A Framework for the Computational Linguistic Analysis of Dehumanization

Frontiers in Artificial Intelligence

Dan Jurafsky¹  Yulia Tsvetkov²  Julia Mendelsohn³ 

[1] Department of Linguistics, Stanford University, Stanford, CA, United States;Language Technologies Institute, Carnegie Mellon University, Pittsburgh, PA, United States;School of Information, University of Michigan, Ann Arbor, MI, United States;

关键词: computational sociolinguistics;    dehumanization;    lexical variation;    language change;    media;    New York Times;   

DOI  :  10.3389/frai.2020.00055

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown