| Title |
Evaluation of Topic Modeling Performance for Overseas Construction Market Analysis Using LDA and BERTopic on News Articles |
| Authors |
백준우(Baik, Joonwoo) ; 정세환(Chung, Sehwan) ; 지석호(Chi, Seokho) |
| DOI |
https://doi.org/10.12652/Ksce.2023.43.6.0811 |
| Keywords |
해외건설; 뉴스 기사; 토픽모델링; Ground truth; 성능평가 Overseas construction; News article; Topic modeling; Ground truth; Performance evaluation |
| Abstract |
Understanding the local conditions is a crucial factor in enhancing the success potential of overseas construction projects. This can be achieved through the analysis of news articles of the target market using topic modeling techniques. In this study, the authors aimed to analyze news articles using two topic modeling methods, namely Latent Dirichlet Allocation (LDA) and BERTopic, in order to determine the optimal approach for market condition analysis. To evaluate the alignment between the generated topics and the actual themes of the news documents, the research collected 6,273 BBC news articles, created ground truth data for individual news article topics, and finally compared this ground truth with the results of the topic modeling. The F1 score for LDA was 0.011, while BERTopic achieved a score of 0.244. These results indicate that BERTopic more accurately reflected the actual topics of news articles, making it more effective for understanding the overseas construction market. |