@inproceedings{ma-etal-2026-narrative,
title = "Narrative Function Patterns in {LLM}-Generated {C}hinese Web Fiction: A Proppian Analysis",
author = "Ma, Yuanchi and
Liu, Jiamou and
Shi, Kaize and
He, Hui and
Zhang, Gang and
Zhao, Zijun and
Hu, Renfen and
Sun, Maosong",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.emnlp-main.1807/",
pages = "41179--41196",
ISBN = "979-8-89176-459-0",
abstract = "Large Language Models (LLMs) have demonstrated remarkable capabilities in narrative generation. However, they often produce structurally homogenized stories, frequently following repetitive arrangements and combinations of plot events along with stereotypical resolutions. In this paper, we propose a novel theoretical framework for analysis by incorporating Proppian narratology and narrative functions. This framework is used to analyze the composition of narrative texts generated by LLMs to uncover their underlying narrative logic. Taking Chinese web literature as our research focus, we extend Propp{'}s narrative theory, defining 34 narrative functions suited to modern web narrative structures. We further construct a human-annotated corpus to support the analysis of narrative structures within LLM-generated text. Experiments reveal that the primary reasons for the singular narrative logic and severe homogenization in generated texts are that current LLMs are unable to correctly comprehend the meanings of narrative functions and instead adhere to rigid narrative generation paradigms."
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%0 Conference Proceedings
%T Narrative Function Patterns in LLM-Generated Chinese Web Fiction: A Proppian Analysis
%A Ma, Yuanchi
%A Liu, Jiamou
%A Shi, Kaize
%A He, Hui
%A Zhang, Gang
%A Zhao, Zijun
%A Hu, Renfen
%A Sun, Maosong
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-459-0
%F ma-etal-2026-narrative
%X Large Language Models (LLMs) have demonstrated remarkable capabilities in narrative generation. However, they often produce structurally homogenized stories, frequently following repetitive arrangements and combinations of plot events along with stereotypical resolutions. In this paper, we propose a novel theoretical framework for analysis by incorporating Proppian narratology and narrative functions. This framework is used to analyze the composition of narrative texts generated by LLMs to uncover their underlying narrative logic. Taking Chinese web literature as our research focus, we extend Propp’s narrative theory, defining 34 narrative functions suited to modern web narrative structures. We further construct a human-annotated corpus to support the analysis of narrative structures within LLM-generated text. Experiments reveal that the primary reasons for the singular narrative logic and severe homogenization in generated texts are that current LLMs are unable to correctly comprehend the meanings of narrative functions and instead adhere to rigid narrative generation paradigms.
%U https://aclanthology.org/2026.emnlp-main.1807/
%P 41179-41196
Markdown (Informal)
[Narrative Function Patterns in LLM-Generated Chinese Web Fiction: A Proppian Analysis](https://aclanthology.org/2026.emnlp-main.1807/) (Ma et al., EMNLP 2026)
ACL
- Yuanchi Ma, Jiamou Liu, Kaize Shi, Hui He, Gang Zhang, Zijun Zhao, Renfen Hu, and Maosong Sun. 2026. Narrative Function Patterns in LLM-Generated Chinese Web Fiction: A Proppian Analysis. In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing, pages 41179–41196, Budapest, Hungary. Association for Computational Linguistics.