The rise in hate speech targeting minority communities underscores the urgent need for effective tools to detect and address harmful content in digital communication. We examine over 3 million tweets posted by state legislators between 2020 and 2021, focusing on messages directed at Asian communities. To address the nuanced nature of hate speech, we develop three comprehensive definitions for identifying hate speech. With human-in-the-loop, our fine-tuned BERT-NLI model achieved improved classification performance. We find that while Anti-Asian tweets comprise only a small portion of legislato...

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