Sentiment Analysis of the Chinese Edition of The Vegetarian Using R

This study aims to analyze the use of emotional vocabulary in Han Kang’s novel The Vegetarian by conducting sentiment analysis on its Chinese edition using the R programming language. Sentiment analysis was performed from three perspectives, and the research findings are summarized as follows:<br/> First, an emotion analysis was conducted on 2,524 emotional vocabulary items obtained through text generation and preprocessing. The results indicated that the emotional tendencies in The Vegetarian were generally balanced between positive and negative sentiments, with a slight predominance of positive sentiment, which exceeded negative sentiment by 1.72 percentage points. The findings regarding emotion types were presented in bar charts, providing intuitive insights and strong visual impact.<br/> Second, polarity analysis involved labeling polarity types for the 2,524 emotional vocabulary items and summing their occurrence frequencies. The results revealed that neutral sentiment accounted for the highest proportion, at 44.01%, while positive and negative sentiments were relatively balanced. However, positive sentiment showed a slight predominance, exceeding negative sentiment by 9.83 percentage points. The analysis results of sentiment polarity were visualized through pie charts, which offered clear and intuitive visual representation.<br/> Third, frequency analysis was performed to visualize the co-occurrence network and word cloud based on the frequency of emotional vocabulary items categorized by emotion and polarity types. Through the co-occurrence network, the study identified keywords and core themes in The Vegetarian, while the word cloud visualization highlighted high-frequency words, demonstrating R’s robust capabilities in data visualization.<br/> The sentiment analysis conducted using R provides an objective framework for examining the use of emotional vocabulary in the novel. This approach contributes to a deeper understanding of Han Kang’s The Vegetarian and showcases a digital methodology for linguistic research. This study is significant in that it bridges traditional Chinese Language and Literature research with the tools and methodologies of the digital age, contributing to the growth of digital Chinese studies. It is hoped that this research will further expand methodological frameworks in Chinese Language and Literature studies and support the ongoing advancement of digital Chinese scholarship.

Authors

Publication Details

Journal
The Journal of Chinese Language and Literature
Published
2025-02-28
DOI
https://doi.org/10.25021/jcll.2025.2.150.57
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sentiment Analysis of the Chinese Edition of The Vegetarian Using R

Liu Liu, Hwa-young Song
The Journal of Chinese Language and Literature
Diverse Approaches in Healthcare and Education Studies
article

Sentiment Analysis of the Chinese Edition of The Vegetarian Using R

Liu Liu, Hwa-young Song
article en

Abstract

This study aims to analyze the use of emotional vocabulary in Han Kang’s novel The Vegetarian by conducting sentiment analysis on its Chinese edition using the R programming language. Sentiment analysis was performed from three perspectives, and the research findings are summarized as follows:<br/> First, an emotion analysis was conducted on 2,524 emotional vocabulary items obtained through text generation and preprocessing. The results indicated that the emotional tendencies in The Vegetarian were generally balanced between positive and negative sentiments, with a slight predominance of positive sentiment, which exceeded negative sentiment by 1.72 percentage points. The findings regarding emotion types were presented in bar charts, providing intuitive insights and strong visual impact.<br/> Second, polarity analysis involved labeling polarity types for the 2,524 emotional vocabulary items and summing their occurrence frequencies. The results revealed that neutral sentiment accounted for the highest proportion, at 44.01%, while positive and negative sentiments were relatively balanced. However, positive sentiment showed a slight predominance, exceeding negative sentiment by 9.83 percentage points. The analysis results of sentiment polarity were visualized through pie charts, which offered clear and intuitive visual representation.<br/> Third, frequency analysis was performed to visualize the co-occurrence network and word cloud based on the frequency of emotional vocabulary items categorized by emotion and polarity types. Through the co-occurrence network, the study identified keywords and core themes in The Vegetarian, while the word cloud visualization highlighted high-frequency words, demonstrating R’s robust capabilities in data visualization.<br/> The sentiment analysis conducted using R provides an objective framework for examining the use of emotional vocabulary in the novel. This approach contributes to a deeper understanding of Han Kang’s The Vegetarian and showcases a digital methodology for linguistic research. This study is significant in that it bridges traditional Chinese Language and Literature research with the tools and methodologies of the digital age, contributing to the growth of digital Chinese studies. It is hoped that this research will further expand methodological frameworks in Chinese Language and Literature studies and support the ongoing advancement of digital Chinese scholarship.

The Journal of Chinese Language and LiteratureVol. 150
Zero hunger
Openalex Percentile: Top 92%
Diverse Approaches in Healthcare and Education Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.