Hyperspherical Semantic Trajectory Analysis Tracks Technology Diffusion

HSTA is an unsupervised methodology that uses Transformer sentence embeddings and Spherical K-Means to track technology diffusion from preprints and patents. By projecting high-dimensional data onto unit hyperspheres, it provides a quantitative metric for tracking breakthroughs before they appear in macroeconomic data.