About how to make novel Visible by using Newly Translated Tale of Genji as an example

TL;DR

This paper employs natural language processing, emotion analysis, and network modeling to visualize and analyze the content and emotional structure of the Newly Translated Tale of Genji, aiming to enhance its visibility and understanding.

Contribution

It introduces a novel approach combining NLP, emotion recognition, and network analysis to visualize and interpret the Tale of Genji in a new way.

Findings

Identified key words in each chapter using tf-did.

Analyzed emotional patterns across chapters.

Mapped relationships between words in the novel.

Abstract

This paper aims to make Tales of Genji visible by using natural language processing, mathematic analysis, emiton analysis. Based on novel, mining data from content of this novel at respect of information abstracting. Summing up the fundamental method of novel visualization, our work are as follows: Based on frequency analysis, we use tf-did to abstract keyword of Newly Translated Tale of Genji, which means the most important word in each chapter. We recognize the emotion of word to analysis the emotion of each chapter of Newly Translated Tale of Genji. Next, we think about the connection between the result of emotion analysis and literature analysis, showing we can get same result by natural language processing. We build a network of all the word apperanced in Newly Translated Tale of Genji. Make a study of relationships between words. Further, we search the writer of Uji Chapters.