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\textbf{Offensive Content Warning}: This paper contains offensive languageonly for providing examples that clarify this research and do not reflect theauthors' opinions. Please be aware that these examples are offensive and maycause you distress.  The subjectivity of recognizing \textit{hate speech} makes it a complex task.This is also reflected by different and incomplete definitions in NLP. Wepresent \textit{hate speech} criteria, developed with perspectives from law andsocial science, with the aim of helping researchers create more precisedefinitions and annotation guidelines on five aspects: (1) target groups, (2)dominance, (3) perpetrator characteristics, (4) type of negative groupreference, and the (5) type of potential consequences/effects. Definitions canbe structured so that they cover a more broad or more narrow phenomenon. Assuch, conscious choices can be made on specifying criteria or leaving themopen. We argue that the goal and exact task developers have in mind shoulddetermine how the scope of \textit{hate speech} is defined. We provide anoverview of the properties of English datasets from \url{hatespeechdata.com}that may help select the most suitable dataset for a specific scenario.

Hate Speech Criteria: A Modular Approach to Task-Specific Hate Speech Definitions