The Role of Big Data in Legal Linguistics: Enhancing Access to Justice through Automated Textual Analysis

Abstract

 The intersection of language and law has traditionally relied on close reading of legal documents, statutes, and case law. In the era of Big Data, however, legal linguistics is undergoing a major transformation as millions of judicial texts, contracts, and online communications become accessible for computational analysis. This study investigates how Big Data transforms media literacy by analyzing digital communication practices from a linguistic perspective.  Drawing on corpora of judicial opinions, legislative records, and online dispute resolution texts, the research employs natural language processing (NLP) and corpus-based methods to analyze legal discourse at scale. Results demonstrate how Big Data enhances the detection of legal ambiguities, improves information retrieval for case law, and supports predictive models for judicial outcomes. Yet, issues of bias, privacy, and algorithmic accountability remain central challenges. The discussion emphasizes that Big Data-driven legal linguistics must balance technological efficiency with principles of fairness and transparency.  Ultimately, the integration of Big Data into legal linguistics holds promise not only for advancing research but also for democratizing access to legal information in society.