THE INTEGRATION OF PHILOLOGY AND DATA SCIENCE: CONTEMPORARY PARADIGMS IN TEXT DATA PROCESSING

Abstract. This paper examines the methodological convergence of philology (particularly English linguistics) and Data Science, tracing this development from the rise of corpus linguistics to the emergence of transformer architectures and LLMs. It critically evaluates how NLP, text mining, and deep learning are applied in English Language Teaching (ELT) — including adaptive learning, automated assessment, and grammatical error detection — and situates these developments within Uzbekistan’s digital education and language technology landscape. Using a narrative and integrative literature review methodology, the study synthesizes evidence from foundational corpus resources, key computational linguistics scholarship, and educational technology research to identify recurring opportunities and limitations. The analysis shows that computational skills are increasingly essential for today’s philologist — not as a replacement for theoretical linguistic knowledge, but as a necessary complement to it. The paper concludes that integrating Data Science into philological training prepares language specialists for the empirical demands of the digital era, while affirming that human linguistic expertise remains central to interpreting and validating computational results.