active project

Linguistic Intergroup Bias

Research on how social-group framing and subtle linguistic choices shape descriptions of people, actions, responsibility, and social meaning.

This research thread uses computational methods to examine linguistic intergroup bias: how descriptions vary with social identity, group membership, agency, abstraction, and evaluative framing. The broader goal is to make patterns in language use inspectable without treating social meaning as a simple classification label.

Role
Research direction and implementation
Period
2024-present
Audience
NLP researchers, social scientists, students

Themes

Skills and Tools

NLPCorpus AnalysisMachine LearningEvaluation

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