LISTN: Lexicon induction with socio-temporal nuance

Research on extremist online communities frequently utilizes linguistic analysis to explore group dynamics and behaviour. Existing studies often rely on outdated lexicons that do not capture the evolving nature of in-group language, nor the social structure of the community. This paper proposes a novel method for inducing in-group lexicons which incorporates its socio-temporal context. Using dynamic word and user embeddings trained on conversations from online anti-women communities, our approach outperforms prior methods for lexicon induction. We provide a new lexicon of manosphere terms, validated by human experts, which quantifies the relevance of each term to a specific sub-community. We present novel insights on in-group language which illustrate the utility of this approach.