Evolution of emotion semantics

TL;DR

This study investigates how emotion word meanings have changed over the past century using NLP on historical texts, revealing that prototypical emotion words are more semantically stable than less representative ones.

Contribution

It demonstrates that prototypicality predicts the rate of semantic change in emotion words, highlighting category-dependent dynamics in semantic evolution.

Findings

Prototypical emotion words change less over time.

Semantic change correlates with prototypicality, frequency, and language.

Category dependence observed in semantic stability of words.

Abstract

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.