Published Paper Details:

The advent of digital humanities has revolutionized the study of literature by integrating computational tools with traditional interpretive methods. This paper explores the application of digital humanities methodologies including text mining, computational linguistics, and digital archiving to analyse literary texts and uncover patterns, trends, and hidden structures that remain elusive through conventional close reading. By employing large-scale text mining techniques, scholars can identify recurring motifs, stylistic markers, and intertextual relationships across extensive corpora. Computational linguistics enables nuanced examinations of language, semantics, and sentiment, offering insights into authorial style, cultural influences, and socio-political contexts. Digital archives further enhance accessibility, enabling researchers to curate, annotate, and preserve vast bodies of literary work while fostering collaborative scholarship. The study emphasizes the complementary nature of distant and close reading, arguing that digital humanities tools do not replace humanistic inquiry but rather augment it with scale, precision, and new interpretive possibilities. Ultimately, this paper demonstrates how computational approaches extend the boundaries of literary analysis, paving the way for innovative scholarship that bridges technology and the humanities.