Climax chapter recognition of a Chinese novel based on plot fluctuation of a chapter and sentiment changing of main character.
Saved in:
| Title: | Climax chapter recognition of a Chinese novel based on plot fluctuation of a chapter and sentiment changing of main character. |
|---|---|
| Authors: | Liu, Zhongbao1 (AUTHOR), Zhang, Bowen1 (AUTHOR), Wan, Guangwen1 (AUTHOR), Zhao, Wenjuan2 (AUTHOR) |
| Source: | Digital Scholarship in the Humanities. Jun2026, Vol. 41 Issue 2, p847-862. 16p. |
| Subjects: | Story plots, Sentiment analysis, Deep learning, Fictional characters, Text mining, Chinese literature |
| Abstract: | The climax chapter of a Chinese novel is the part where the conflict develops to be tense and sharp. Such a chapter determines the fate of the main character, the development of the plot, and the end of the story, which makes it crucial to a Chinese novel. How to quickly and accurately recognize the climax chapter is important to attract readers' interest. The climax chapter of a Chinese novel has two distinctive characteristics: dramatic development of plot fluctuation and sentiment changing of the main character. Therefore, this paper tries to propose a model to recognize the climax chapter, which both considers the plot fluctuation of a chapter and the sentiment changing of the main character on the corpus The Legend of the Condor Heroes (射雕英雄传), based on a series of deep learning models. The plot fluctuation of a chapter and the sentiment changing of the main character can be, respectively, depicted as plot fluctuation curve of a chapter and sentiment changing curve of the main character. The chapter difference curve can be drawn by combining the above two curves and based on which the novel climax chapter can be determined. Comparative experimental results on the experimental corpus show that, compared to existing models, the performance of the model proposed in this paper is much better, its F1 value arriving at 87.50 per cent. Ablation experiment results show that the F1 value of the model considering sentiment changing of main character is 9.41 per cent higher than that of the model considering the plot fluctuation of a chapter. [ABSTRACT FROM AUTHOR] |
| 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.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 194636953 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Climax chapter recognition of a Chinese novel based on plot fluctuation of a chapter and sentiment changing of main character. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Liu%2C+Zhongbao%22">Liu, Zhongbao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Bowen%22">Zhang, Bowen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wan%2C+Guangwen%22">Wan, Guangwen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhao%2C+Wenjuan%22">Zhao, Wenjuan</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Digital+Scholarship+in+the+Humanities%22">Digital Scholarship in the Humanities</searchLink>. Jun2026, Vol. 41 Issue 2, p847-862. 16p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Story+plots%22">Story plots</searchLink><br /><searchLink fieldCode="DE" term="%22Sentiment+analysis%22">Sentiment analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink><br /><searchLink fieldCode="DE" term="%22Fictional+characters%22">Fictional characters</searchLink><br /><searchLink fieldCode="DE" term="%22Text+mining%22">Text mining</searchLink><br /><searchLink fieldCode="DE" term="%22Chinese+literature%22">Chinese literature</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The climax chapter of a Chinese novel is the part where the conflict develops to be tense and sharp. Such a chapter determines the fate of the main character, the development of the plot, and the end of the story, which makes it crucial to a Chinese novel. How to quickly and accurately recognize the climax chapter is important to attract readers' interest. The climax chapter of a Chinese novel has two distinctive characteristics: dramatic development of plot fluctuation and sentiment changing of the main character. Therefore, this paper tries to propose a model to recognize the climax chapter, which both considers the plot fluctuation of a chapter and the sentiment changing of the main character on the corpus The Legend of the Condor Heroes (射雕英雄传), based on a series of deep learning models. The plot fluctuation of a chapter and the sentiment changing of the main character can be, respectively, depicted as plot fluctuation curve of a chapter and sentiment changing curve of the main character. The chapter difference curve can be drawn by combining the above two curves and based on which the novel climax chapter can be determined. Comparative experimental results on the experimental corpus show that, compared to existing models, the performance of the model proposed in this paper is much better, its F1 value arriving at 87.50 per cent. Ablation experiment results show that the F1 value of the model considering sentiment changing of main character is 9.41 per cent higher than that of the model considering the plot fluctuation of a chapter. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>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.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=194636953 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/llc/fqag034 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 847 Subjects: – SubjectFull: Story plots Type: general – SubjectFull: Sentiment analysis Type: general – SubjectFull: Deep learning Type: general – SubjectFull: Fictional characters Type: general – SubjectFull: Text mining Type: general – SubjectFull: Chinese literature Type: general Titles: – TitleFull: Climax chapter recognition of a Chinese novel based on plot fluctuation of a chapter and sentiment changing of main character. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liu, Zhongbao – PersonEntity: Name: NameFull: Zhang, Bowen – PersonEntity: Name: NameFull: Wan, Guangwen – PersonEntity: Name: NameFull: Zhao, Wenjuan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 2055768X Numbering: – Type: volume Value: 41 – Type: issue Value: 2 Titles: – TitleFull: Digital Scholarship in the Humanities Type: main |
| ResultId | 1 |
