Subdiffusive semantic evolution in Indo-European languages

TL;DR

This study reveals that semantic change in Indo-European languages follows a universal subdiffusive pattern, indicating constrained and anomalously slow evolution of word meanings over time.

Contribution

The paper demonstrates that semantic evolution is universally subdiffusive across five major Indo-European languages, using a novel diachronic semantic embedding pipeline and stochastic modeling.

Findings

Semantic change follows a subdiffusive pattern with an exponent of about 0.45.

Preserving temporal correlations is essential to observe subdiffusive behavior.

Subdiffusion remains robust under various data analysis methods.

Abstract

How do words change their meaning? Although semantic evolution is driven by a variety of distinct factors, including linguistic, societal, and technological ones, we find that there is one law that holds universally across five major Indo-European languages: that semantic evolution is strongly subdiffusive. Using an automated pipeline of diachronic distributional semantic embedding that controls for underlying symmetries, we show that words follow stochastic trajectories in meaning space with an anomalous diffusion exponent $\alpha= 0.45\pm 0.05$ across languages, in contrast with diffusing particles that follow $\alpha=1$. Randomization methods indicate that preserving temporal correlations in semantic change directions is necessary to recover strongly subdiffusive behavior; however, correlations in change sizes play an important role too. We furthermore show that strong subdiffusion is a robust phenomenon under a wide variety of choices in data analysis and interpretation, such as the choice of fitting an ensemble average of displacements or averaging best-fit exponents of individual word trajectories.