Digital Humanities in English Literature: Bridging Traditional Textual Analysis With Modern Technology

Digital Humanities (DH) has emerged as a transformative approach in English literary studies by integrating computational tools with traditional literary analysis. This paper examines the application of DH tools such as text mining, sentiment analysis, and data visualisation in analysing recurrent themes, emotional dynamics, and narrative developments in literary texts. Through two case studies—text mining in Shakespearean tragedies and sentiment analysis in Victorian novels—the paper demonstrates how these tools reveal new interpretive possibilities. The first case study applies keyword frequency analysis and thematic clustering in Shakespearean tragedies, highlighting motifs such as ambition, betrayal, and fate. The second case study uses sentiment analysis metrics like polarity and subjectivity to trace emotional arcs in Charles Dickens’s Great Expectations and Thomas Hardy’s Tess of the d’Urbervilles. Findings show that computational methods enhance literary interpretation by enabling large-scale textual analysis and visual representations of complex relationships. The broader implications of DH, including its potential in artificial intelligence, blockchain for text preservation, and augmented reality, are also discussed. Ethical considerations such as data privacy and intellectual property rights are critically examined. DH promotes an interdisciplinary approach that advances research and literary scholarship pedagogy by integrating computational analysis with human interpretive skills.