👉 Literature computing, also known as computational linguistics or natural language processing (NLP) in the context of literature, refers to the application of computational techniques and algorithms to analyze, understand, and generate human language as it appears in literary texts. This interdisciplinary field combines methods from computer science, linguistics, and literature to explore complex textual data, uncover hidden patterns, and extract meaningful insights from vast corpora of literary works. From sentiment analysis to topic modeling, machine learning models, and deep learning architectures, literature computing aims to automate and enhance various aspects of literary analysis, such as authorship attribution, stylistic comparison, and thematic exploration. By bridging the gap between human language and computational tools, literature computing not only aids scholars and researchers in their studies but also opens up new avenues for creative expression and digital humanities.
