A Distant Reading Study of Marriage Discourse in Jane Austen’s Novels Using Thematic Modeling

Authors

  • Le Jing International Cultural and Educational College, Northeast Agricultural University, Harbin, Heilongjiang, 150030, China
  • Yali Yang International Cultural and Educational College, Northeast Agricultural University, Harbin, Heilongjiang, 150030, China

DOI:

https://doi.org/10.70917/ijcisim-2026-2363

Keywords:

TF-IDF; LDA topic modeling; sentiment analysis; Jane Austen; discourse on marriage

Abstract

Jane Austen’s works primarily explore women’s perspectives on marriage and express the pursuit of female independence, making them masterpieces of feminist literary criticism. This study uses textual data from the complete works of Jane Austen’s six representative novels as its data source. It employs the TF-IDF algorithm for text feature analysis, utilizes semantic network graphs to visualize high-frequency words in the text, and applies the LDA topic model to identify four major themes of marital discourse in Jane Austen’s novels. Finally, it analyzes the feminist themes from the perspective of emotional shifts across the chapters of the novels. The study found that the discourse on marriage in Jane Austen’s novels can be categorized into four major themes: the emotional and rational dynamics of marriage; the economic and social class constraints of marriage; the essence of marital happiness and the pursuit of value; and the influence of family and social opinion on marriage. Austin’s feminist thought, shaped by emotional structures, manifests both progressive and conservative aspects. The emotional values across the chapters of her novels are influenced by her feminist ideology—which embodies both progressiveness and limitations—and evolve through the interplay of positive and negative emotions.

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Published

2026-06-27

How to Cite

Le Jing, & Yali Yang. (2026). A Distant Reading Study of Marriage Discourse in Jane Austen’s Novels Using Thematic Modeling. International Journal of Computer Information Systems and Industrial Management Applications, 18, 11. https://doi.org/10.70917/ijcisim-2026-2363

Issue

Section

Original Articles