Geometric Structures and Patterns of Meaning: A PHATE Manifold Analysis of Chinese Character Embeddings
This provides computational evidence for linguistic theories and establishes a framework for analyzing semantic organization, though it is incremental as it applies existing methods to a specific domain.
The study investigated geometric patterns in Chinese character embeddings using PHATE manifold analysis, finding that meaningful characters show rich geometric diversity while structural radicals form tight clusters, with geometric complexity correlating with semantic content across over 1000 characters and 12 domains.
We systematically investigate geometric patterns in Chinese character embeddings using PHATE manifold analysis. Through cross-validation across seven embedding models and eight dimensionality reduction methods, we observe clustering patterns for content words and branching patterns for function words. Analysis of over 1000 Chinese characters across 12 semantic domains reveals that geometric complexity correlates with semantic content: meaningful characters exhibit rich geometric diversity while structural radicals collapse into tight clusters. The comprehensive child-network analysis (123 phrases) demonstrates systematic semantic expansion from elemental character. These findings provide computational evidence supporting traditional linguistic theory and establish a novel framework for geometric analysis of semantic organization.