JOURNAL ARTICLE

Research on the psychology of fictional characters based on artificial intelligence—an example study on The Family.

  • Published In: Digital Scholarship in the Humanities, 2023, v. 38, n. 2. P. 798 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Yuan, Ying 3 of 3

Abstract

This article focuses on applying ecological recognition technology based on artificial intelligence to analyze the big-five personality traits of main characters in Ba Jin's novel *The Family*. Using the Chinese psychological analysis system "Text Mind," which integrates natural language processing and a psychoanalytic dictionary, the study quantitatively predicts personality scores from characters' dialog texts and validates these results against existing literary analyses and plot descriptions. The findings show that the predicted personality traits of characters Jue-Xin, Jue-Hui, and Qin align with their literary portrayals, reflecting differences influenced by traditional and modern ideological trends. This method offers an objective, data-driven supplement to traditional literary criticism by reducing subjectivity in character analysis.

Additional Information

  • Source:Digital Scholarship in the Humanities. 2023/06, Vol. 38, Issue 2, p798
  • Document Type:Article
  • Subject Area:Literature and Writing
  • Publication Date:2023
  • ISSN:2055-768X
  • DOI:10.1093/llc/fqac058
  • Accession Number:164367973
  • Copyright Statement:Copyright of Digital Scholarship in the Humanities is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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