Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

January 31, 2024


Pages


DOI

Article

Constructing a Theory of Affective Stylistics in Modern Chinese Literature Based on Knowledge Mapping


Authors

Zhiyong Wang Affiliation:
School of Literature and Media, Zhongyuan Institute of Science and Technology, Xuchang, Henan, 461000, China.


Abstract

Emotion stylistics is an important bridge to communicate the emotions of characters and the emotions of readers in modern Chinese literature. This paper extends the emotion dictionary based on the point mutual information in the SOPMI algorithm and introduces the emotion words into the emotion dictionary to calculate the emotion values of modern Chinese literature texts. Modern Chinese literature’s emotions can be visualized through knowledge filtering, knowledge fusion, and text classification modules of the knowledge graph. Multimodal theory is used to construct a theoretical framework that is dynamic and multimodal stylistic. The study focuses on the emotional intensity, tendency, flow, and visualization analysis of The Divine Eagle Warrior, a modern Chinese literature, as the research object. The results show that the emotional density of the original work is 0.107, the amount of both positive and negative emotions reaches about 3, and the maximum fluctuation of emotions in the whole text is 0.23. The results reveal the structural composition of emotions in the discourse of modern Chinese literature, which is of great reference significance for further understanding the nature of literature and constructing the theory of emotional stylistics.


Keywords

SO-PMI algorithm, Emotion lexicon, Knowledge map, Dynamic multimodality, Emotion stylistics, 01A25


Citation

Wang, Z. (2024). Constructing a theory of affective stylistics in modern chinese literature based on knowledge mapping. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-0075

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