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Annotator Disagreement by wgd25281 is a document available to read on EtoBox.
This paper addresses the challenge of annotator disagreement in hate speech classification, particularly in Turkish tweets, emphasizing the importance of high-quality labeled data for effective machine learning models. It evaluates various strategies to manage disagreements among annotators and proposes a novel method for deriving true labels, ultimately providing state-of-the-art results in hate speech detection. The research contributes to the understanding of subjective labeling tasks and aims to improve
- Author
- wgd25281
- Language
- EN