Anthology of Computers and the Humanities · Volume 3

Detecting “Parasitic Poems”: Quantifying Poetic Style in Late Imperial Chinese Fiction

Jiayu Liu1 ORCID , Rongqian Ma2 ORCID and Keli Du3 ORCID

  • 1 Department of Statistics, College of Liberal Arts & Sciences, University of Illinois Urbana-Champaign, Champaign, IL, USA
  • 2 Department of Information and Library Science, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA
  • 3 Trier Center for Digital Humanities, University of Trier, Trier, Germany
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Permanent Link: https://doi.org/10.63744/N0PaywVKs6GJ

Published: 21 November 2025

Keywords: Late imperial Chinese fiction, parasitic poems, computational literary analysis

Abstract

Embedded poetry is a defining feature of late imperial Chinese fiction, yet its narrative function remains contested. While some critics regard these poems as “parasitic”—reiterating surrounding prose with minimal contribution—others argue for their integral aesthetic and rhetorical roles. This study aims to explore if parasitic poems exist in late imperial Chinese fiction and how they can be systematically identified. We develop a computational framework to detect such poems across a corpus of Qing-dynasty novels, combining proxy-based measures (cosine similarity and mutual information) with prompt-based large language models (LLMs). Using a manually annotated dataset of 300 poem-context pairs, we evaluate each method’s alignment with human judgments. Our preliminary findings show that proxy models achieve higher accuracy but exhibit limited sensitivity to nonparasitic cases. A multilingual prompt-based approach yields a more balanced performance, suggesting LLMs can approximate literary interpretation when effectively prompted. Our work offers tools for analyzing Chinese poetry and demonstrates the potential of LLMs in modeling literary analysis.