한국수소및신에너지학회논문집 (Transactions of the Korean hydrogen and new energy society)

  • 제33권2호
  • /
  • Pages.121-129
  • /
  • 2022
  • /
  • 1738-7264(pISSN)
  • /
  • 2288-7407(eISSN)
한국수소및신에너지학회 (The Korean Hydrogen and New Energy Society)
권호 표지
DOI QR코드

DOI QR Code

뉴스 빅데이터를 활용한 수소 이슈 탐색

A Study on Social Issues for Hydrogen Industry Using News Big Data

  • 투고 : 2022.01.13
  • 심사 : 2022.04.09
  • 발행 : 2022.04.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

With the advent of the post-2020 climate regime, the hydrogen industry is growing rapidly around the world. In order to build the hydrogen economy, it is important to identify social issues related to hydrogen and prepare countermeasures for them. Accordingly, this study conducted a semantic network analysis on hydrogen news from NAVER. As a result of the analysis, the number of hydrogen news in 2020 increased by 4.5 times compared to 2016, and as of 2018, the hydrogen issue has shifted from an environmental aspect to an economic aspect. In addition, although the initial government-led hydrogen industry is expanding to the mobility field such as privately-led fuel cell electric vehicles and hydrogen fuel, terms showing concerns about the safety such as explosions are constantly being exposed. Thus, it is necessary not only to expand the hydrogen ecosystem through the participation of private companies, but also to promote hydrogen safety.

키워드

참고문헌

  1. Hydrogen Council, "Hydrogen scaling up: a sustainable pathway for the global energy transition", Hydrogen Council, 2017. Retrieved from https://hydrogencouncil.com/wp-content/uploads/2017/11/Hydrogen-scaling-up-HydrogenCouncil.pdf.
  2. J. S. Park and P. S. Yeoun, "A network analysis on the forest healing issues using big data - focused on Korean web news from 2005 to 2019 -", The Journal of Korean Institute of Forest Recreation, Vol. 24, No. 2, 2020, pp. 63-71, doi: https://doi.org/10.34272/forest.2020.24.2.006.
  3. B. W. Kang, T. H. Kim, and T. H. Lee, "Analysis of costs for a hydrogen refueling station in Korea", Trans Korean Hydrogen New Energy Soc, Vol. 27, No. 3. 2016, pp. 256-263, doi: http://dx.doi.org/10.7316/KHNES.2016.27.3.256.
  4. B. J. Kim, "An economic analysis of the hydrogen station enterprise considering dynamic utilization", Trans Korean Hydrogen New Energy Soc, Vol. 28, No. 1, 2017, pp. 47-55, doi: https://doi.org/10.7316/KHNES.2017.28.1.47.
  5. B. J. Kim and J. W. Kim, "An analysis of the economy of scale for domestic on-site hydrogen fueling stations", Journal of Energy Engineering, Vol. 16, No. 4, 2007, pp. 170-180. Retrieved from http://www.koreascience.or.kr/article/JAKO200707341597329.pub.
  6. B. J. Kim, W. L. Yoon, and D. J. Seo, "Analysis of the economy of scale for domestic steam methane reforming hydrogen refueling stations utilizing the scale factor", Trans Korean Hydrogen New Energy Soc, Vol. 30, No. 3, 2019, pp. 251-259, doi: https://doi.org/10.7316/KHNES.2019.30.3.251.
  7. B. I. Choe, "A Korean strategy for the hydrogen society infrastructure based on the liquefied hydrogen", Superconductivity and Cryogenics, Vol. 22, No. 1, 2020, pp. 9-12. Retrieved from https://www.earticle.net/Article/A370584.
  8. J. H. Han, S. J. Kim, and C. B. Kim, "A strategy development of hydrogen energy industrial infrastructure by using SWOT/AHP method", Journal of Korea Technology Innovation Society, Vol. 19, No. 4, 2016, pp. 822-847. Retrieved from https://www.koreascience.or.kr/article/JAKO201610364778833.j.
  9. Y. Y. Kim, J. S. Park, and J. S. Jeong, "A study on overseas case analysis and empirical analysis for the development of the hydrogen industry in Chungcheongbuk-do", International Business Review, Vol. 24, No. 2, 2020, pp. 77-90. Retrieved from http://www.kaibm.or.kr/html/sub0303.html?pageNm=article&journal=1&code=378914&issue=28464&Page=2&year=2020&searchType=title&searchValue=. https://doi.org/10.21739/ibr.2020.06.24.2.77
  10. S. K. Kang, Y. S. Huh, and J. S. Moon, "A study on safety improvement for packaged hydrogen refueling station by risk assessment", Trans Korean Hydrogen New Energy Soc, Vol. 28, No. 6, 2017, pp. 635-641, doi: https://doi.org/10.7316/KHNES.2017.28.6.635.
  11. K. W. Rhie, T. H. Kim, and T. H. Lee, "Quantitative safety assessment for hydrogen station dispenser", Trans Korean Hydrogen New Energy Soc, Vol. 17, No. 3, 2006, pp. 272-278. Retrieved from https://www.hydrogen.or.kr/upload/papers/KHNES.Vol.17,No.03-05.pdf.
  12. J. S. Jeong, M. K. Jee, M. H. Go, H. D. Kim, H. Y. Lim, Y. R. Lee, and W. I. Kim, "Related documents classification system by similarity between documents", Journal of Broadcast Engineering, Vol. 24, No. 1, 2019, pp. 77-86, doi: https://doi.org/10.5909/JBE.2019.24.1.77.
  13. P. Bafna, D. Pramod, and A. Vaidya, "Document clustering: TF-IDF approach", 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), 2016, pp. 61-66, doi: https://doi.org/10.1109/ICEEOT.2016.7754750.
  14. D. Kim, D. Seo, S. Cho, and P. Kang, "Multi-co-training for document classification using various document representations: TF-IDF, LDA, and Doc2Vec", Information Sciences, Vol. 477, 2019, pp. 15-29, doi: https://doi.org/10.1016/j.ins.2018.10.006.
  15. B. K. Jeon and H. C. Ahn, "A collaborative filtering system combined with users' review mining : application to the recommendation of smartphone apps", J. Intell. Inform. Syst., Vol. 21, No. 2, 2015, pp. 1-18, doi: https://doi.org/10.13088/jiis.2015.21.2.01.
  16. R. Iwabuchi, Y. Nakajima, H. Honma, H. Aoshima, A. Kobayashi, T. Akiba, and S. Masuyama, "Proposal of recommender system based on user evaluation and cosmetic ingredients", 2017 International Conference on Advanced Informatics, Concepts, Theory, and Applications (ICAICTA), 2017, pp. 1-6, doi: https://doi.org/10.1109/ICAICTA.2017.8090967.
  17. Z. K. Zhang, T. Zhou, and Y. C. Zhang, "Tag-aware recommender systems: a state-of-the-art survey". Journal of Computer Science and Technology, Vol. 26, 2011, pp. 767, doi: https://doi.org/10.1007/s11390-011-0176-1.
  18. Z. H. Deng, K. H. Luo, and H. L. Yu, "A study of supervised term weighting scheme for sentiment analysis", Expert Systems with Applications, Vol. 41, No. 7, 2014, pp. 3506-3513, doi: https://doi.org/10.1016/j.eswa.2013.10.056.
  19. M. Rathi, A. Malik, D. Varshney, R. Sharma, and S. Mendiratta, "Sentiment analysis of tweets using machine learning approach", 2018 Eleventh International Conference on Contemporary Computing (IC3), 2018, pp. 1-3, doi: https://doi.org/10.1109/IC3.2018.8530517.
  20. S. S. Lee, "A content analysis of journal articles using the language network analysis methods", Journal of the Korean Society for Information Management, Vol. 31, No. 4, 2014, pp. 49-68, doi: https://doi.org/10.3743/KOSIM.2014.31.4.049.
  21. M. Yoo, S. Lee, and T. Ha, "Semantic network analysis for understanding user experiences of bipolar and depressive disorders on Reddit", Information Processing & Management, Vol. 56, No. 4, 2019, pp. 1565-1575, doi: https://doi.org/10.1016/j.ipm.2018.10.001.
  22. J. Choi and Y. S. Hwang, "Patent keyword network analysis for improving technology development efficiency", Technological Forecasting and Social Change, Vol. 83, 2014, pp. 170-182, doi: https://doi.org/10.1016/j.techfore.2013.07.004.
  23. B. Yoon and Y. Park, "A text-mining-based patent network: analytical tool for high-technology trend", The Journal of High Technology Management Research, Vol. 15, No. 1, 2004, pp. 37-50, doi: https://doi.org/10.1016/j.hitech.2003.09.003.
  24. S. Duari and V. Bhatnagar, "Complex network based supervised keyword extractor", Expert Systems with Applications, Vol. 140, 2020, pp. 112876, doi: https://doi.org/10.1016/j.eswa.2019.112876.
  25. H. J. Seo, "The issues deduction of the payment system by the text network analysis", Journal of Payment and Settlement Vol. 10, No. 2, 2018, pp. 37-64. Retrieved from https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002419261.
  26. H. J. Seo, "Identifying key issues in Korea's defense policy - application of text network analysis to the 2018 defense white paper -", Korean Journal of Military Affairs, Vol. 6, 2019, pp. 39-70, doi: https://doi.org/10.33528/kjma.2019.12.6.39.
  27. H. J. Lee and Y. O. Kang, "Understanding tourist's region of attraction and image of city through social network data analysis", Journal of the Korean Urban Geographical Society, Vol. 23, No. 1, 2020, pp. 101-114, doi: http://dx.doi.org/10.21189/JKUGS.23.1.8.
  28. S. H. Cho, "A study on analysis of the trend of blockchain by key words network analysis", Journal of Korea Institute of Information, Electronics, and Communication Technology, Vol. 11, No. 5, 2018, pp. 550-555, doi: https://doi.org/10.17661/jkiiect.2018.11.5.550.