# Verifying Claims About Metaphors with Large-Scale Automatic Metaphor Identification

arXiv: https://arxiv.org/abs/2404.01029 · HTML: https://mlsanity.com/paper/2404.01029/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 33 references that are in the map.
- First posted on arXiv 1 Apr 2024.

## Builds on (most cited first, 6 of 6)

- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification](https://mlsanity.com/paper/2010.12421/) (2020)
- [DynaSent: A Dynamic Benchmark for Sentiment Analysis](https://mlsanity.com/paper/2012.15349/) (2020)
- [MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories](https://mlsanity.com/paper/2104.13615/) (2021)
- [A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification](https://mlsanity.com/paper/1810.05754/) (2018)
- [Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddings](https://mlsanity.com/paper/1807.02903/) (2018)

## Built on by (most cited first, 1 of 1)

- [CoMet: Metaphor-Driven Covert Communication for Multi-Agent Language Games](https://mlsanity.com/paper/2505.18218/) (2025)

## 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.