mlsanityData to 7 Oct 2026

Inducing lexicons of in-group language with socio-temporal context

arXiv 2409.19257 ↗First posted 28 Sep 2024cs.CL cs.SIcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 9 of its 25 references that are in the map. First posted on arXiv 28 Sep 2024.

Builds on

9 of 25 references.

References · 9

  1. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
  2. 2017Neural Collaborative Filteringcited by 1,108
  3. 2018Augmenting Neural Response Generation with Context-Aware Topical Attentioncited by 27
  4. 2023From Dogwhistles to Bullhorns: Unveiling Coded Rhetoric with Language Modelscited by 26
  5. 2021Characterizing English Variation across Social Media Communities with BERTcited by 20
  6. 2018Making "fetch" happen: The influence of social and linguistic context on nonstandard word growth and declinecited by 15
  7. 2024Building Knowledge-Guided Lexica to Model Cultural Variationcited by 11
  8. 2018The Road to Success: Assessing the Fate of Linguistic Innovations in Online Communitiescited by 9
  9. 2023Identity Construction in a Misogynist Incels Forumcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.