mlsanityData to 7 Oct 2026

Features of Perceived Metaphoricity on the Discourse Level: Abstractness and Emotionality

arXiv 2205.08939 ↗First posted 18 May 2022cs.CLcited by 4

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Abstract (arXiv)

Research on metaphorical language has shown ties between abstractness and emotionality with regard to metaphoricity; prior work is however limited to the word and sentence levels, and up to date there is no empirical study establishing the extent to which this is also true on the discourse level. This paper explores which textual and perceptual features human annotators perceive as important for the metaphoricity of discourses and expressions, and addresses two research questions more specifically. First, is a metaphorically-perceived discourse more abstract and more emotional in comparison to a literally-perceived discourse? Second, is a metaphorical expression preceded by a more metaphorical/abstract/emotional context than a synonymous literal alternative? We used a dataset of 1,000 corpus-extracted discourses for which crowdsourced annotators (1) provided judgements on whether they perceived the discourses as more metaphorical or more literal, and (2) systematically listed lexical terms which triggered their decisions in (1). Our results indicate that metaphorical discourses are more emotional and to a certain extent more abstract than literal discourses. However, neither the metaphoricity nor the abstractness and emotionality of the preceding discourse seem to play a role in triggering the choice between synonymous metaphorical vs. literal expressions. Our dataset is available at https://www.ims.uni-stuttgart.de/data/discourse-met-lit.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 2 of its 67 references that are in the map. First posted on arXiv 18 May 2022.

Builds on

2 of 67 references.

References · 2

  1. 2020Learning and Evaluating Emotion Lexicons for 91 Languagescited by 13
  2. 2018Emotion Representation Mapping for Automatic Lexicon Construction (Mostly) Performs on Human Levelcited by 7

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Citing papers per year: 2022: 1; 2023: 1; 2024: 2.

4 papers.