Mapping Societal Anxiety from the Industrial Era to the AI Age: A Computational Sentiment Analysis of Victorian Literature and Digital Discourse

The rapid acceleration of artificial intelligence and automated systems in the modern era has reignited widespread debate regarding technological displacement, economic alienation, and human redundancy. This paper presents a comparative computational sentiment analysis bridging nineteenth-century industrial literature with contemporary digital discourse on automation. Using Charles Dickens’ Hard Times (1854) as a thematic anchor for First Industrial Revolution anxieties, we analyze literary text against a curated corpus of modern public discourse surrounding artificial intelligence. Employing Python-based Natural Language Processing (NLP) tools—specifically the NLTK VADER sentiment analysis engine, alongside Matplotlib and Seaborn for statistical data visualization—this study quantifies polarity, compound sentiment distributions, and semantic shifts across both eras. The findings demonstrate striking structural parallels between Victorian anti-industrial alienation and contemporary AI existential dread, confirming that human resistance to structural automation follows recurring socio-psychological patterns.