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Hate in the United States today is narrowly understood but widely used as a politically charged term. Recently, political blame-placing on outsiders such as immigrants has bred a climate of hate and provided fuel for organizations that promote hostility toward others based on marginal group identification. This study investigates patterns of hate groups across space and their drivers with respect to socioeconomic and ideological variables for counties in the United States. Linear and spatial filtering with eigenvector (SFE) models are used to infer relationships between socioeconomic and ideological variables and the number of hate groups within U.S. counties. Additionally, geographically weighted regression (GWR) is used to identify spatial patterns of those relationships. We find that distinct regions of hate can be delineated with variations of hate group activity according to the independent and control variables employed.
Medina et al. (Fri,) studied this question.