LISTN: Lexicon induction with socio-temporal nuance
–arXiv.org Artificial Intelligence
In-group language is an important signifier of group dynamics. This paper proposes a novel method for inducing lexicons of in-group language, which incorporates its socio-temporal context. Existing methods for lexicon induction do not capture the evolving nature of in-group language, nor the social structure of the community. Using dynamic word and user embeddings trained on conversations from online anti-women communities, our approach outperforms prior methods for lexicon induction. We develop a test set for the task of lexicon induction and a new lexicon of manosphere language, validated by human experts, which quantifies the relevance of each term to a specific sub-community at a given point in time. Finally, we present novel insights on in-group language which illustrate the utility of this approach.
arXiv.org Artificial Intelligence
Dec-11-2024
- Country:
- Africa > Central African Republic
- Ombella-M'Poko > Bimbo (0.04)
- North America > United States
- New Mexico > Santa Fe County > Santa Fe (0.04)
- Oceania > Australia (0.04)
- Africa > Central African Republic
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- Research Report (1.00)
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- Health & Medicine (0.68)
- Law Enforcement & Public Safety (0.93)
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