  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.
