Corpus Based

Corpus-based research utilizes large collections of text and speech data to investigate various linguistic phenomena, aiming to uncover patterns and relationships not readily apparent through traditional methods. Current research focuses on applying statistical methods and machine learning models, including generalized additive models, random forests, and various deep learning architectures, to analyze diverse aspects of language, from tonal variations in speech to the prevalence of bias in online text. This approach yields valuable insights into language structure, usage, and evolution, informing fields like computational linguistics, natural language processing, and the social sciences, and providing data-driven support for linguistic theories.