Evolution of emotion semantics
Not on the map. Why?
Abstract (arXiv)
Humans possess the unique ability to communicate emotions through language. Although concepts like anger or awe are abstract, there is a shared consensus about what these English emotion words mean. This consensus may give the impression that their meaning is static, but we propose this is not the case. We cannot travel back to earlier periods to study emotion concepts directly, but we can examine text corpora, which have partially preserved the meaning of emotion words. Using natural language processing of historical text, we found evidence for semantic change in emotion words over the past century and that varying rates of change were predicted in part by an emotion concept's prototypicality - how representative it is of the broader category of "emotion". Prototypicality negatively correlated with historical rates of emotion semantic change obtained from text-based word embeddings, beyond more established variables including usage frequency in English and a second comparison language, French. This effect for prototypicality did not consistently extend to the semantic category of birds, suggesting its relevance for predicting semantic change may be category-dependent. Our results suggest emotion semantics are evolving over time, with prototypical emotion words remaining semantically stable, while other emotion words evolve more freely.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 54 references that are in the map. First posted on arXiv 5 Aug 2021.
Builds on
7 of 54 references.
References · 7
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
- 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
- 2016Semantics derived automatically from language corpora contain human-like biasescited by 894
- 2016Diachronic Word Embeddings Reveal Statistical Laws of Semantic Changecited by 219
- 2014Statistically Significant Detection of Linguistic Changecited by 82
- 2020Sentiment Analysis: Automatically Detecting Valence, Emotions, and Other Affectual States from Textcited by 26
- 2020Text-based inference of moral sentiment changecited by 11
Built on by
Not cited yet.