A common factor in bias measurement methods is the use of hand-curated seed lexicons, but there remains little guidance for their selection. We gather seeds used in prior work, documenting their common sources and rationales, and in case studies of three English-language corpora, we enumerate the different types of social biases and linguistic features that, once encoded in the seeds, can affect subsequent bias measurements. Seeds developed in one context are often re-used in other contexts, but documentation and evaluation remain necessary precursors to relying on seeds for sensitive measurements.

Bad Seeds: Evaluating Lexical Methods for Bias Measurement

**Session Chair: ** Kai-Wei Chang 
**Session Volunteer: ** Ronald Seoh

4E: Ethics in NLP #1

technical paper

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