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Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang ...
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Abstract:
Languages are continuously undergoing changes, and the mechanisms that underlie these changes are still a matter of debate. In this work, we approach language evolution through the lens of causality in order to model not only how various distributional factors associate with language change, but how they causally affect it. In particular, we study slang, which is an informal language that is typically restricted to a specific group or social setting. We analyze the semantic change and frequency shift of slang words and compare them to those of standard, nonslang words. With causal discovery and causal inference techniques, we measure the effect that word type (slang/nonslang) has on both semantic change and frequency shift, as well as its relationship to frequency, polysemy and part of speech. Our analysis provides some new insights in the study of semantic change, e.g., we show that slang words undergo less semantic change but tend to have larger frequency shifts over time. ... : Accepted as a main conference paper at ACL 2022 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2203.04651
https://dx.doi.org/10.48550/arxiv.2203.04651
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Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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Bird's Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact ...
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How Good Is NLP?A Sober Look at NLP Tasks through the Lens of Social Impact ...
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“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding ...
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Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations ...
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Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations ...
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Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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How Good Is NLP?A Sober Look at NLP Tasks through the Lens of Social Impact
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In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021)
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Differentiable subset pruning of transformer heads
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In: Transactions of the Association for Computational Linguistics, 9 (2021)
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Scaling Within Document Coreference to Long Texts
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In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021)
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“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding
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In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations
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In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (2021)
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