Large-scale statistical analysis of four harmful language datasets reveals that interactions between annotator characteristics and linguistic cues drive annotation variation, with lexical features and attitudes prominent but patterns varying by dataset.
D 3 CODE : Disentangling Disagreements in Data across Cultures on Offensiveness Detection and Evaluation
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Who and What? Using Linguistic Features and Annotator Characteristics to Analyze Annotation Variation
Large-scale statistical analysis of four harmful language datasets reveals that interactions between annotator characteristics and linguistic cues drive annotation variation, with lexical features and attitudes prominent but patterns varying by dataset.