@article{ART003383551},
author={Tae-Min Lee and Jeon-Young Kong and Woong Kim},
title={Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2026},
volume={31},
number={9},
pages={259-269}
TY - JOUR
AU - Tae-Min Lee
AU - Jeon-Young Kong
AU - Woong Kim
TI - Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling
JO - Journal of The Korea Society of Computer and Information
PY - 2026
VL - 31
IS - 9
PB - The Korean Society Of Computer And Information
SP - 259
EP - 269
SN - 1598-849X
AB - This study analyzed major discourses in the esports industry using TF-IDF and LDA topic modeling.
The dataset comprised 40 KIPRIS patents, 289 KeSPA press releases, and 171 Global Esports news articles. Preprocessing included regular-expression-based token extraction, stop-word removal, orthographic normalization, and compound-term preservation. English candidate terms were mapped to representative Korean concepts, and source-specific mean TF-IDF scores were L1-normalized and combined with equal weights to identify key terms. For LDA, the 500 original documents were retained as individual units, with adjustments for document length and source imbalance. Topic models containing two to ten topics were evaluated using coherence, perplexity, diversity, and stability. The analysis identified three source-associated topics: technology and data services, domestic leagues and talent development, and global cooperation and governance. This study contributes by comparing esports-industry discourses across multiple sources while limiting its interpretation to the collected dataset.
KW - eSports;TF-IDF;LDA;Topic Modeling;Web Crawling;Text Mining
DO -
UR -
ER -
Tae-Min Lee, Jeon-Young Kong and Woong Kim. (2026). Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling. Journal of The Korea Society of Computer and Information, 31(9), 259-269.
Tae-Min Lee, Jeon-Young Kong and Woong Kim. 2026, "Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling", Journal of The Korea Society of Computer and Information, vol.31, no.9 pp.259-269.
Tae-Min Lee, Jeon-Young Kong, Woong Kim "Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling" Journal of The Korea Society of Computer and Information 31.9 pp.259-269 (2026) : 259.
Tae-Min Lee, Jeon-Young Kong, Woong Kim. Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling. 2026; 31(9), 259-269.
Tae-Min Lee, Jeon-Young Kong and Woong Kim. "Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling" Journal of The Korea Society of Computer and Information 31, no.9 (2026) : 259-269.
Tae-Min Lee; Jeon-Young Kong; Woong Kim. Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling. Journal of The Korea Society of Computer and Information, 31(9), 259-269.
Tae-Min Lee; Jeon-Young Kong; Woong Kim. Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling. Journal of The Korea Society of Computer and Information. 2026; 31(9) 259-269.
Tae-Min Lee, Jeon-Young Kong, Woong Kim. Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling. 2026; 31(9), 259-269.
Tae-Min Lee, Jeon-Young Kong and Woong Kim. "Analysis of eSports Industry Trends Using TF-IDF and LDA Topic Modeling" Journal of The Korea Society of Computer and Information 31, no.9 (2026) : 259-269.
