Recent research on dehumanization

204 citations recorded by the source corpus.

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Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection (2021, background): “Dehumanization Content which ‘perceiv[es] or treat[s] people as less than human’ (Haslam and Stratemeyer, 2016).”
A Framework for the Computational Linguistic Analysis of Dehumanization (2020, background): “At the core of this issue is dehumanization, “the act of perceiving or treating people as less than human” (Haslam and Stratemeyer, 2016), a process that heavily contributes to extreme intergroup bias (Haslam, 2006).”
Implicitly Abusive Language – What does it actually look like and why are we not getting there? (2021, background): “While Haslam and Loughnan (2016) propose a fairly comprehensive set of different properties that characterize de-humanization, we focus on the most commonly accepted property of likening members of the target group to non-human entities (Haslam, 2006), such as machines, animals or diseases.”
On Measures of Biases and Harms in NLP (2021, background): “…actively casts disfavored groups as “others” and aims to erase signs of shared humanity (e.g. emotions, agency, intelligence), thus suppressing opportunities for empathy with said “out group” by characterizing them as sub-human (Markowitz and Slovic, 2020; Haslam and Stratemeyer, 2016).”