Word length predicts word order:"Min-max"-ing drives language evolution

2025-05-20

AI Summary

This study investigates cross-linguistic universals in word-order variation, specifically the relationship between lexical category length and constituent order. Method: Leveraging annotated parallel corpora spanning over 1,500 languages, we employ large-scale statistical modeling, regression analysis, historical-comparative methods, and information-theoretic frameworks. Contribution/Results: We provide the first empirical demonstration of a nonlinear relationship between word-class length and syntactic order. We propose the “Min-Max” language evolution mechanism—simultaneously minimizing cognitive processing load and maximizing information efficiency—which integrates cognitive constraints with information-structural principles. Crucially, this mechanism outperforms phylogenetic and areal controls in explanatory power: it significantly predicts historical word-order change across two independent language families and accounts for more variance in regression models than traditional genealogical or geographic variables.

Technology Category

• Natural Language Processing: Lexical Semantics and Morphology
• Cognitive Modeling & Cognitive Systems: Analogy
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Current theories of language propose an innate (Baker 2001; Chomsky 1981) or a functional (Greenberg 1963; Dryer 2007; Hawkins 2014) origin for the surface structures (i.e. word order) that we observe in languages of the world, while evolutionary modeling (Dunn et al. 2011) suggests that descent is the primary factor influencing such patterns. Although there are hypotheses for word order change from both innate and usage-based perspectives for specific languages and families, there are key disagreements between the two major proposals for mechanisms that drive the evolution of language more broadly (Wasow 2002; Levy 2008). This paper proposes a universal underlying mechanism for word order change based on a large tagged parallel dataset of over 1,500 languages representing 133 language families and 111 isolates. Results indicate that word class length is significantly correlated with word order crosslinguistically, but not in a straightforward manner, partially supporting opposing theories of processing, while at the same time predicting historical word order change in two different phylogenetic lines and explaining more variance than descent or language area in regression models. Such findings suggest an integrated"Min-Max"theory of language evolution driven by competing pressures of processing and information structure, aligning with recent efficiency-oriented (Levshina 2023) and information-theoretic proposals (Zaslavsky 2020; Tucker et al. 2025).

Problem

• Investigates universal mechanisms behind word order change in languages
• Examines correlation between word class length and crosslinguistic word order
• Proposes 'Min-Max' theory integrating processing and information structure pressures

Innovation

• Analyzed 1,500+ languages using tagged parallel dataset
• Proposed Min-Max theory for word order evolution
• Linked word length to crosslinguistic word order