Defense Issue Analysis Using BERT and LDA Topic Modeling: Focused on Defense Innovation 4.0
- Authors
- Park, Doohong; Kang, Donggoo; Paik, Joonki
- Issue Date
- Jan-2024
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Defense Innovation 4.0; KeyBERT; LDA; SentenceBERT; similarity comparison
- Citation
- 2024 International Conference on Electronics, Information, and Communication, ICEIC 2024
- Journal Title
- 2024 International Conference on Electronics, Information, and Communication, ICEIC 2024
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/73329
- DOI
- 10.1109/ICEIC61013.2024.10457191
- ISSN
- 0000-0000
- Abstract
- Defense Innovation 4.0 is the current government's defense reform plan. In this paper, we focused on how much impact Defence Innovation 4.0 had on news reporting. To achieve this, we first collected defense-related articles for one year before and after the announcement of the national agenda. Then we extract set of keywords of the article using the Key BERT model. Based on these keywords, we analyze how major defense issues changed using Latent Dirichlet Allocation (LDA) topic modeling. In addition to analyzing how major defense issues changed using LDA topic modeling and conducting a SentenceBERT-based similarity comparison with the core content of the Defense Innovation 4.0 master plan. Through our research, we seek to gain valuable insights into how Defense Innovation 4.0 has influenced the discourse around defense-related topics within the media landscape. © 2024 IEEE.
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Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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