Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang

• URL: http://arxiv.org/abs/2203.04651v1
• Date: Wed, 9 Mar 2022 11:34:43 GMT
• Title: Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang
• Authors: Daphna Keidar, Andreas Opedal, Zhijing Jin, Mrinmaya Sachan
• Abstract summary: We study slang, 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. We show that slang words undergo less semantic change but tend to have larger frequency shifts over time.
• Score: 18.609276255676175
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

Related papers

• Correlation Does Not Imply Compensation: Complexity and Irregularity in the Lexicon [48.00488140516432]
  We find evidence of a positive relationship between morphological irregularity and phonotactic complexity within languages. We also find weak evidence of a negative relationship between word length and morphological irregularity.
  arXiv  Detail & Related papers  (2024-06-07T18:09:21Z)
• Survey in Characterization of Semantic Change [0.1474723404975345]
  Understanding the meaning of words is vital for interpreting texts from different cultures. Semantic changes can potentially impact the quality of the outcomes of computational linguistics algorithms.
  arXiv  Detail & Related papers  (2024-02-29T12:13:50Z)
• Syntactic Language Change in English and German: Metrics, Parsers, and Convergences [56.47832275431858]
  The current paper looks at diachronic trends in syntactic language change in both English and German, using corpora of parliamentary debates from the last c. 160 years. We base our observations on five dependencys, including the widely used Stanford Core as well as 4 newer alternatives. We show that changes in syntactic measures seem to be more frequent at the tails of sentence length distributions.
  arXiv  Detail & Related papers  (2024-02-18T11:46:16Z)
• Reliable Detection and Quantification of Selective Forces in Language Change [3.55026004901472]
  We apply a recently-introduced method to corpus data to quantify the strength of selection in specific instances of historical language change. We show that this method is more reliable and interpretable than similar methods that have previously been applied.
  arXiv  Detail & Related papers  (2023-05-25T10:20:15Z)
• Neighboring Words Affect Human Interpretation of Saliency Explanations [65.29015910991261]
  Word-level saliency explanations are often used to communicate feature-attribution in text-based models. Recent studies found that superficial factors such as word length can distort human interpretation of the communicated saliency scores. We investigate how the marking of a word's neighboring words affect the explainee's perception of the word's importance in the context of a saliency explanation.
  arXiv  Detail & Related papers  (2023-05-04T09:50:25Z)
• Crosslinguistic word order variation reflects evolutionary pressures of dependency and information locality [4.869029215261254]
  About 40% of the world's languages have subject-verb-object order, and about 40% have subject-object-verb order. We show that variation in word order reflects different ways of balancing competing pressures of dependency locality and information locality. Our findings suggest that syntactic structure and usage across languages co-adapt to support efficient communication under limited cognitive resources.
  arXiv  Detail & Related papers  (2022-06-09T02:56:53Z)
• Quantifying Cognitive Factors in Lexical Decline [2.4424095531386234]
  We propose a variety of psycholinguistic factors -- semantic, distributional, and phonological -- that we hypothesize are predictive of lexical decline. We find that most of our proposed factors show a significant difference in the expected direction between each curated set of declining words and their matched stable words. Further diachronic analysis reveals that declining words tend to decrease in the diversity of their lexical contexts over time, gradually narrowing their 'ecological niches'
  arXiv  Detail & Related papers  (2021-10-12T07:12:56Z)
• Fake it Till You Make it: Self-Supervised Semantic Shifts for Monolingual Word Embedding Tasks [58.87961226278285]
  We propose a self-supervised approach to model lexical semantic change. We show that our method can be used for the detection of semantic change with any alignment method. We illustrate the utility of our techniques using experimental results on three different datasets.
  arXiv  Detail & Related papers  (2021-01-30T18:59:43Z)
• Lexical semantic change for Ancient Greek and Latin [61.69697586178796]
  Associating a word's correct meaning in its historical context is a central challenge in diachronic research. We build on a recent computational approach to semantic change based on a dynamic Bayesian mixture model. We provide a systematic comparison of dynamic Bayesian mixture models for semantic change with state-of-the-art embedding-based models.
  arXiv  Detail & Related papers  (2021-01-22T12:04:08Z)
• Where New Words Are Born: Distributional Semantic Analysis of Neologisms and Their Semantic Neighborhoods [51.34667808471513]
  We investigate the importance of two factors, semantic sparsity and frequency growth rates of semantic neighbors, formalized in the distributional semantics paradigm. We show that both factors are predictive word emergence although we find more support for the latter hypothesis.
  arXiv  Detail & Related papers  (2020-01-21T19:09:49Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.