Earticle

초록

영어

The rise of the internet and smartphones has transformed the web novel industry into a significant cultural force. Platforms like Naver Series and Kakao Page experienced explosive growth, soaring from KRW 10 billion to KRW 640 billion from 2013 to 2020 and surpassing KRW 1 trillion by 2022. With approximately 5.87 million readers[1], this growth is expected to continue, fueled by global exports to Japan and China. In this competitive landscape, platforms enhance user experiences using features like 'keywords' to ensure user loyalty. This study employs text mining to analyze character combinations in top-ranking romance fantasy web novels, aiming to unveil user preferences and correlations, providing valuable insights into the webnovel domain.

목차

Abstract
Introduction
Data & Preprocessing
Methods
Results
Exploratory Data Analysis (EDA)
Ranking Download Score
Conclusion
References

저자

• Elisa Choi [ Hanyang University, School of Business, Department of Business Informatics ]
• Haneul Kim [ Hanyang University, School of Business, Department of Business Informatics ]

참고문헌