Big Data and the Transformation of Media Literacy: Linguistic Insights into Digital Communication Practices

Abstract

 The digital revolution has reshaped how media is produced, consumed, and interpreted, presenting new challenges and opportunities for media literacy. In the era of Big Data, vast amounts of linguistic and multimodal data are generated through social media platforms, news portals, and online interactions.  This study investigates how Big Data transforms media literacy by analyzing digital communication practices from a linguistic perspective.  Drawing upon large-scale corpora of online discourse, the research employs computational and discourse-analytic methods to explore patterns of language use, misinformation, and participatory communication. Results reveal how Big Data enhances the capacity to detect narrative framing, identify misinformation, and understand audience engagement. At the same time, ethical concerns regarding privacy, data bias, and algorithmic influence raise critical questions about equitable access to digital knowledge. The findings suggest that media literacy, when supported by Big Data analytics, transcends traditional critical reading skills and evolves into a dynamic competence that integrates linguistic analysis, critical thinking, and digital ethics.  This transformation has significant implications for education, public discourse, and democratic participation in an increasingly datafied world.