Language Change

Language change, the dynamic evolution of linguistic structures and usage, is a complex process studied through computational modeling and large-scale data analysis. Current research focuses on understanding the interplay of social factors, learning mechanisms (including supervised and unsupervised learning in iterated learning models), and the impact of noise and multilingual contexts on language evolution, often employing large language models (LLMs) and novel algorithms like contrastive decoding and elastic reset for analysis and prediction. These investigations are significant for advancing our understanding of language as a dynamic system and have practical implications for applications such as automated language processing, detecting neurological disorders through speech analysis, and mitigating the effects of language drift in online content moderation.