한국멀티미디어학회논문지 (Journal of Korea Multimedia Society)

  • 제25권10호
  • /
  • Pages.1483-1498
  • /
  • 2022
  • /
  • 1229-7771(pISSN)
  • /
  • 2384-0102(eISSN)
한국멀티미디어학회 (Korea Multimedia Society)
권호 표지
DOI QR코드

DOI QR Code

자연어 처리를 활용한 메타버스 보도, 연구 간 인식 차이 비교

Utilizing Natural Language Processing to Compare Perceptions of Metaverse between News Articles and Academic Research

  • Lee, Gyuho (Department of Communication., Seoul National University) ;
  • Lee, Joonhwan (Department of Communication., Seoul National University)
  • 투고 : 2022.06.24
  • 심사 : 2022.09.23
  • 발행 : 2022.10.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

While public interests in the metaverse are growing recently in the Korean media and research, its understanding has not been fully established yet. In this study, we aimed to probe whether the rapid growth in media attention about the metaverse has increased its usage as a buzzword accompanied by an absence of scientific context. We analyzed publications and online news containing "metaverse" from 2020 to 2022. The data analysis methods are 1) time series frequency, 2) keyword network, 3) natural language model. The findings indicate the perception gap about metaverse between research and news articles broadened as its popularity has grown. Research about metaverse gradually expanded its connections with related topics-virtual and augmented realities-focusing on social changes in a remote environment. However, media reporting frequently used "metaverse" as a buzzword rather than explaining its scientific background, stimulating the proliferation of related topics and the dispersion of news content. This study further discusses the need for a media strategy to improve public conception of the long-term development of the metaverse.

키워드

과제정보

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2021S1A5B8096358)

참고문헌

  1. M.G. Pellechia, "Trends in Science Coverage: A Content Analysis of Three US Newspapers," Public Understanding of Science, Vol. 6, No. 1, p. 49, 1997. https://doi.org/10.1088/0963-6625/6/1/004
  2. S.W. Song and D.-H. Chung, "Explication and Rational Conceptualization of Metaverse," Informatization P olicy, Vol. 28, No. 3, pp. 3-22, 2021.
  3. Macromill Trendmonitor, (2022), https://www.trendmonitor.co.kr/tmweb/trend/allTrend/detail.do?bIdx=2309&code=0404&trendType=CKOREA, (accessed June 1, 2022).
  4. S. Han and T. Kim, "News Big Data Analysis of 'Metaverse' Using Topic Modeling Analysis," Journal of Digital Contents Society, Vol. 22, No. 7, pp. 1091-1099, 2021. https://doi.org/10.9728/dcs.2021.22.7.1091
  5. C.-S. Kim, Y. Lee, and H. Ahn, "A Study on the Metaverse: Focused on the Application of News Big Data Service and Case Study," Journal of Korea Society of Digital Industry and Information Management, Vol. 17, No. 2, pp. 85-101, 2021. https://doi.org/10.17662/KSDIM.2021.17.2.085
  6. T. Kim, B. Ahn, W. Lee, and H. Kang, "Analysis of Metaverse Trends Using News Big Data," Journal of Digital Contents Society, Vol. 23, No. 2, pp. 203-216, 2022. https://doi.org/10.9728/dcs.2022.23.2.203
  7. B. Winston, Media, Technology and Society: A History: From the Telegraph to the Internet, Routledge Publishers, Abingdon: Oxfordshire, 2002.
  8. Science and Scientists Held in High Esteem Across Global Publics, Pew Research Center, Washington, D.C. (2020), https://www.pewresearch.org/science/2020/09/29/science-andscientists-held-in-high-esteem-acrossglobal-publics/ (accessed June 1, 2022).
  9. B.G. Southwell and A. Torres, "Connecting Interpersonal and Mass Communication: Science News Exposure, Perceived Ability to Understand Science, and Conversation," Communication Monographs, Vol. 73, No. 3, pp. 334-350, 2006. https://doi.org/10.1080/03637750600889518
  10. R.M. Entman, "Framing: Towards clarification of a fractured paradigm," McQuail's Reader in Mass Communication Theory, Vol. 390, p. 397, 1993.
  11. G. Tuchman, Making News: A Study in the Construction of Reality, Free Press Publishers, New York, 1978.
  12. V.D. Blondel, J.-L. Guillaume, R. Lambiotte, and E. Lefebvre, "Fast Unfolding of Communities in Large Networks," Journal of Statistical Mechanics: Theory and Experiment, Vol. 2008, No. 10, p. P10008, 2008. https://doi.org/10.1088/1742-5468/2008/10/P10008
  13. J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, "Bert: Pre-Training of Deep Bidirectional Transformers for Language Understanding," arXiv Preprint, arXiv:1810.04805, 2018.
  14. T. Mikolov, K. Chen, G. Corrado, and J. Dean, "Efficient Estimation of Word Representations in Vector Space," arXiv Preprint, arXiv:1301.3781, 2013.
  15. Korea Press Foundation, 2021 Press Auidence Survey, Korea Press Foundation Publishers, Seoul, 2021.
  16. M. Lee and M. Song, "Incorporating Citation Impact into Analysis of Research Trends," Scientometrics, Vol. 124, No. 2, pp. 1191-1224, 2020. https://doi.org/10.1007/s11192-020-03508-3