[2F5-OS-39b] OS-39

[2F5-OS-39b-04] Analysis of Emotional Changes During Story Progression of Popular Web Novels Using SHAP

〇Makoto Watanabe¹, Yusuke Fukazawa¹ (1. Sophia University)

Keywords:SHAP, BERT, sentiment analysis, novels, text mining

This study aims to clarify the differences between popular and general works in the emotional characteristics of stories and how they change throughout story progression. Text data were collected from the "Shousetsuka ni Narou" website, with the top 300 works based on global points categorized as popular works and 300 randomly selected works as general works. BERT was then used to conduct sentence-level sentiment analysis, and the texts were divided into fixed-length segments, using the average sentiment score as a feature. Based on these features, a classification model was constructed using Random Forest to distinguish between popular and general works. Finally, SHAP analysis was conducted to reveal the emotional tendencies of the works. The analysis results indicated that the emotional balance of a story significantly influences readers’ emotional engagement and satisfaction. In particular, during the early stages, emotions such as sadness and anticipation related to the main character’s problem-solving play a crucial role in drawing readers into the story. Towards the end, popular works tend to maintain emotions related to anticipation and trust as the story progresses, while emotions such as surprise and fear gradually decrease.