Computational Literary Studies (CLS) emerged in the mid-20th century with early stylometric analyses, such as Frederick Mosteller and David Wallace’s 1964 study on the authorship of The Federalist Papers.

The field gained momentum in the 1990s and early 2000s with Franco Moretti’s “distant reading” approach, which used computational methods to analyze large literary corpora, challenging traditional close reading. The rise of natural language processing (NLP), machine learning, and digital humanities further expanded CLS, enabling topic modeling, sentiment analysis, and network analysis of texts.

Today, CLS continues to evolve, integrating AI and large-scale text analysis to explore literature in ways previously unimaginable, while also sparking debates on the balance between quantitative methods and human interpretation.

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