DOI QR코드

DOI QR Code

A Methodology for Analyzing Public Opinion about Science and Technology Issues Using Text Analysis

텍스트 분석을 활용한 과학기술이슈 여론 분석 방법론

  • 김다솜 (국민대학교 비즈니스IT전문대학원) ;
  • ;
  • 임명수 (국민대학교 비즈니스IT전문대학원) ;
  • 류신 (국민대학교 비즈니스IT전문대학원) ;
  • 김남규 (국민대학교 경영정보학부) ;
  • 박준형 (실전전략연구소) ;
  • 길우영 (실전전략연구소) ;
  • 윤한술 (실전전략연구소)
  • Received : 2015.07.26
  • Accepted : 2015.09.04
  • Published : 2015.09.30

Abstract

Recently, many users frequently share their opinions on diverse issues using various social media. Therefore, many governments have attempted to establish or improve national policies according to the public opinions captured from the various social media. In this paper, we indicate several limitations of traditional approaches for analyzing public opinions about science and technology and provide an alternative methodology to overcome the limitations. First of all, we distinguish science and technology analysis phase and social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we apply a start list and a stop list successively to acquire clarified and interesting results. Finally, to identify most appropriate documents fitting to a given subject, we develop a new concept of logical filter that consists of not only mere keywords but also a logical relationship among keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discovering core issues and public opinions from 1,700,886 documents comprising SNS, blog, news, and discussion.

Keywords

References

  1. Bae, J.H., J.E. Son, and M. Song, "Analysis of Twitter for 2012 South Korea Presidential Election by Text Mining Techniques", Journal of Intelligence and Information Systems, Vol.19, No.3, 2013, 141-156. (배정환, 손지은, 송민, "텍스트 마이닝을 이용한 2012년 한국대선 관련 트위터 분석", 지능정보연구, 제19권, 제3호, 2013, 141-156.) https://doi.org/10.13088/jiis.2013.19.3.141
  2. Gartner, "2012 Hype Cycle for Emerging Technologies", Gartner Inc., Stamford, 2012.
  3. Huang, S., W. Peng, J. Li, and D. Lee, "Sentiment and Topic Analysis on Social Media : a Multi-task Multi-label Classification Approach", Proceedings of the 5th Annual ACM Web Science Conference, 2013, 172-181.
  4. Hyun, Y.J., N.K. Kim, and Y.H. Cho, "A Multi-Dimensional Issue Clustering from the Perspective Consumers' Interests and R&D", Journal of Information Technology Services, Vol.14, No.1, 2015, 237-249. (현윤진, 김남규, 조윤호, "소비자 선호 이슈 및 R&D 관점에서의 다차원 이슈 클러스터링", 한국IT서비스학회지, 제14권, 제1호, 2014, 237-249.)
  5. Jeong, C.W. and J.J. Kim, "Analysis of Trend in Construction Using Textmining method", Journal of The Korean Digital Architecture.Interior Association, Vol.12, No.2, 2012, 53-60. (정철우, 김재준, "텍스트마이닝을 활용한 건설분야 트랜드 분석", 한국디지털건축인테리어학회논문집, 제12권, 제2호, 2012, 53-60.)
  6. Kim, H.J., N.O. Jo, and K.S. Shin, "Text Mining-Based Emerging Trend Analysis for the Aviation Industry", Journal of Intelligence and Information Systems, Vol.21, No.1, 2015, 65-82. (김현정, 조남옥, 신경식, "항공산업 미래유망 분야 선정을 위한 텍스트 마이닝 기반의 트렌드 분석", 지능정보연구, 제21권, 제1호, 2015, 65-82.) https://doi.org/10.13088/jiis.2015.21.1.65
  7. Kim, J.E., N.K Kim, and Y.H. Cho, "User-Perspective Issue Clustering Using Multi-Layered Two-Mode Network Analysis", Journal of Intelligence and Information Systems, Vol.20, No.2, 2014, 93-107. (김지은, 김남규, 조윤호, "다계층 이원 네트워크를 활용한 사용자 관점의 이슈 클러스터링", 지능 정보연구, 제20권, 제2호, 2014, 93-107.) https://doi.org/10.13088/JIIS.2014.20.2.093
  8. Korea Internet and Security Agency, "2014 Korea Internet White Paper", Korea Internet and Security Agency, 2014.
  9. Kwahk, K.Y., "Social Network Analysis", Cheongram, Seoul, 2014.
  10. Lee, T.B. and C.J. Lee, "A Study on the Identifying Emerging Defense Technology using S&T Text Mining", Journal of the Military Operations Research Society of Korea, Vol.36, No.1, 2010, 39-49. (이태봉, 이춘주, "S&T Text Mining을 이용한 국방 유망기술 식별에 관한 연구", 한국국방경영분석학회지, 제36권, 제1호, 2010, 39-49.)
  11. Lim, M.S. and N.K. Kim, "Analyzing the Issue Life Cycle by Mapping Inter-Period Issues", Journal of Intelligence and Information Systems, Vol.20, No.4, 2014, 25-41. (임명수, 김남규, "기간별 이슈 매핑을 통한 이슈 생명주기 분석 방법론", 지능정보연구, 제20권, 제4호, 2014, 25-41.) https://doi.org/10.13088/jiis.2014.20.4.25
  12. McKinsey Global Institute, "Big Data : The next Frontier for Innovation, Competition, and Productivity", McKinsey and Company, 2011.
  13. Min, K.Y., H.T. Kim, and Y.G. Ji, "A Pilot Study on Applying Text Mining Tools to Analyzing Steel Industry Trends : A Case Study of the Steel Industry for the Company 'P'", Journal of Society for e-Business Studies, Vol.19, No.3, 2014, 51-64. (민기영, 김훈태, 지용구, "철강산업 트렌드 분석을 위한 텍스트 마이닝 도입 연구-P社 사례를 중심으로", 한국전자거래학회지, 제19권, 제3호, 2014, 51-64.) https://doi.org/10.7838/jsebs.2014.19.3.051
  14. Son, Y.H., I.K. Kim, and N.G. Kim, "Automated Conceptual Data Modeling Using Association Rule Mining", The Journal of Information Systems, Vol.18, No.4, 2009, 59-86. (손윤호, 김인규, 김남규, "연관규칙 마이닝을 활용한 개념적 데이터베이스 설계 자동화 기법", 정보시스템연구, 제18권, 제4호, 2009, 59-86.) https://doi.org/10.5859/KAIS.2009.18.4.059
  15. Witten, I.H., "Text Mining : Practical Handbook of Internet Computing", CRC Press, Florida, 2005.