CLSISep 28, 2024

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

arXiv:2409.19257v32 citationsh-index: 2
Originality Incremental advance
AI Analysis

This addresses the need for better tools to analyze evolving group dynamics in online communities, though it appears incremental as it builds on existing lexicon induction methods.

The paper tackles the problem of inducing lexicons of in-group language by incorporating socio-temporal context, outperforming prior methods using dynamic word and user embeddings from online anti-women communities, and creates a validated lexicon of manosphere language with quantified term relevance.

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.

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