Diachronic Semantic

Diachronic semantics investigates how word meanings evolve over time, aiming to understand the processes and patterns of semantic change. Current research focuses on developing and refining computational models, including rule-based systems, neural networks (like transformer architectures), and generative models incorporating word embeddings, to analyze large text corpora across different historical periods. These advancements enable more accurate detection and quantification of semantic shifts, offering valuable insights into language evolution and informing historical linguistics, lexicography, and potentially even the development of more robust natural language processing systems.