mlsanityData to 7 Oct 2026

Verifying Claims About Metaphors with Large-Scale Automatic Metaphor Identification

arXiv 2404.01029 ↗First posted 1 Apr 2024cs.CLcited by 1

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Abstract (arXiv)

There are several linguistic claims about situations where words are more likely to be used as metaphors. However, few studies have sought to verify such claims with large corpora. This study entails a large-scale, corpus-based analysis of certain existing claims about verb metaphors, by applying metaphor detection to sentences extracted from Common Crawl and using the statistics obtained from the results. The verification results indicate that the direct objects of verbs used as metaphors tend to have lower degrees of concreteness, imageability, and familiarity, and that metaphors are more likely to be used in emotional and subjective sentences.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 33 references that are in the map. First posted on arXiv 1 Apr 2024.

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References · 6

  1. 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 719
  2. 2020TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classificationcited by 414
  3. 2020DynaSent: A Dynamic Benchmark for Sentiment Analysiscited by 63
  4. 2021MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theoriescited by 46
  5. 2018A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplificationcited by 24
  6. 2018Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddingscited by 10

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