Abstract

This paper explores the application of sentiment analysis techniques to understand the emotional landscape of Victorian literature. By analyzing a corpus of key Victorian novels, the study aims to uncover patterns of melancholy, joy, anger, and other emotions, providing insights into the socio-cultural context of the 19th century. The research employs natural language processing tools to quantify and visualize emotional trends, examining how these reflect the broader themes of industrialization, social change, and personal identity in Victorian England. Through this computational approach, the study contributes to both digital humanities and literary scholarship, offering a novel perspective on the emotional dimensions of classic literary works.

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