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Investigating Lexical Change through Cross-Linguistic Colexification Patterns

Kim Gfeller, Sabine Stoll, Chundra Cathcart, Paul Widmer

TL;DR

This study investigates how lexical meaning shifts, as captured by colexification patterns, unfold across deep time using phylogenetic models. By modeling stationary probabilities and change speeds for concept pairs with predictors of associativity, frequency, and borrowability, it analyzes three language families (Austronesian, Indo-European, Uralic) to identify general versus family-specific dynamics. Key findings show that more closely related concepts colexify more and change more slowly, while higher frequency and borrowability modulate rates in a non-uniform, cross-family manner, highlighting the role of areal and cultural context. The work demonstrates the utility of combining synchronic colexification data with temporally explicit models to reveal long-term biases in semantic evolution and suggests extending the framework to include contact and broader semantic domains.

Abstract

One of the most intriguing features of language is its constant change, with ongoing shifts in how meaning is expressed. Despite decades of research, the factors that determine how and why meanings evolve remain only partly understood. Colexification -- the phenomenon of expressing multiple distinct concepts using the same word form -- serves as a valuable window onto the dynamics of meaning change across languages. Here, we apply phylogenetic comparative models to dictionary data from three language families, Austronesian, Indo-European, and Uralic, in order to shed light on the evolutionary dynamics underlying the colexification of concept pairs. We assess the effects of three predictors: associativity, borrowability, and usage frequency. Our results show that more closely related concept pairs are colexified across a larger portion of the family tree and exhibit slower rates of change. In contrast, concept pairs that are more frequent and more prone to borrowing tend to change more rapidly and are less often colexified. We also find considerable differences between the language families under study, suggesting that areal and cultural factors may play a role.

Investigating Lexical Change through Cross-Linguistic Colexification Patterns

TL;DR

This study investigates how lexical meaning shifts, as captured by colexification patterns, unfold across deep time using phylogenetic models. By modeling stationary probabilities and change speeds for concept pairs with predictors of associativity, frequency, and borrowability, it analyzes three language families (Austronesian, Indo-European, Uralic) to identify general versus family-specific dynamics. Key findings show that more closely related concepts colexify more and change more slowly, while higher frequency and borrowability modulate rates in a non-uniform, cross-family manner, highlighting the role of areal and cultural context. The work demonstrates the utility of combining synchronic colexification data with temporally explicit models to reveal long-term biases in semantic evolution and suggests extending the framework to include contact and broader semantic domains.

Abstract

One of the most intriguing features of language is its constant change, with ongoing shifts in how meaning is expressed. Despite decades of research, the factors that determine how and why meanings evolve remain only partly understood. Colexification -- the phenomenon of expressing multiple distinct concepts using the same word form -- serves as a valuable window onto the dynamics of meaning change across languages. Here, we apply phylogenetic comparative models to dictionary data from three language families, Austronesian, Indo-European, and Uralic, in order to shed light on the evolutionary dynamics underlying the colexification of concept pairs. We assess the effects of three predictors: associativity, borrowability, and usage frequency. Our results show that more closely related concept pairs are colexified across a larger portion of the family tree and exhibit slower rates of change. In contrast, concept pairs that are more frequent and more prone to borrowing tend to change more rapidly and are less often colexified. We also find considerable differences between the language families under study, suggesting that areal and cultural factors may play a role.
Paper Structure (24 sections, 4 equations, 2 figures, 4 tables)

This paper contains 24 sections, 4 equations, 2 figures, 4 tables.

Table of Contents

  1. Introduction
  2. Dynamics of colexification
  3. Associativity
  4. Frequency of use
  5. Borrowability
  6. Data
  7. Concept pairs and colexifications
  8. Predictors
  9. Associativity scores
  10. Frequency scores
  11. Borrowability scores
  12. Language phylogenies
  13. Methods
  14. Rate inference and regression
  15. Model Validation
  16. ...and 9 more sections

Figures (2)

  • Figure 1: Interactions between colexification data and changes in meaning of words. Vertical dashed lines represent changes that are captured by our approach.
  • Figure 2: Posterior samples of the regression coefficients