The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
권호 표지
DOI QR코드

DOI QR Code

Analysis of the Perception of Autonomous Vehicles Using Text Mining Technique

텍스트 마이닝 기법을 활용한 자율주행자동차 인식분석연구

  • 임이정 (홍익대학교 도시계획과) ;
  • 송재인 (홍익대학교 도시계획과) ;
  • 이자영 (홍익대학교 도시계획과) ;
  • 황기연 (홍익대학교 도시공학과)
  • Received : 2017.11.15
  • Accepted : 2017.12.08
  • Published : 2017.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this study is to improve the social acceptance of AVs by analyzing the citizen's perception using an emotional analysis technique which belongs to a type of text mining. The source of the data is originated from 3 year accumulated internet articles and comments on AV from 164 newspapers and Naver. According to the study results, there exists a positive perception on AVs, although negative ones are more frequent than the positive. Also most of people take neutral position on AV due to the unfamiliarity and lack of experience on AVs And these problems needs to be responded before AV's commercialization through continuous analyses on the perception and social acceptance.

자율주행자동차는 미래 교통수단으로써 주목받고 있으며, 전 세계적으로 관련 기술 개발 및 수용성 연구가 진행되고 있다. 그러나 자율주행자동차와 같은 신기술의 수용에 대한 인식조사는 부족한 실정이다. 이에 본 연구에서는 자율주행자동차의 법제화와 상용화를 위한 기반 조성 작업의 일환으로 인터넷 기사와 댓글을 활용하여 텍스트 마이닝 기법 중 감성평가기법을 적용하여 자율주행자동차에 대한 시민들의 인식분석연구를 수행하였다. 분석 결과, 자율주행자동차에 대한 긍정적인 시각도 있으나 부정적인 인식이 더 큰 것으로 나타났으며, 대부분 유보적인 판단을 내리는 것으로 나타났다. 이는 자율주행자동차 기술의 불확실성, 탑승 경험 부족으로 인한 것이라 판단되었으며, 사회적 수용성 향상을 위해 도입 이전 해소되어야 할 문제라 사료된다. 또한 지속적인 인식조사 및 설문조사를 통해 사회적 수용성을 확보할 방안을 강구해야할 필요가 있을 것으로 판단된다.

Keywords

References

  1. Eo D. S.(2015), Comparison of Learning Methods in Text Mining with Big Data, Department of Data Science Graduate School, Inje University.
  2. Heo C. and Ohn S. Y.(2017), "A Novel Method for Constructing Sentiment Dictionaries using Word2vec and Label Propagation," The Journal of Korean Institute of Next Generation Computing, vol. 13, no. 2, pp.93-101.
  3. Jang K. A., Park S. H. and Kim W. J.(2015), "Automatic Construction of a Negative/positive Corpus and Emotional Classification using the Internet Emotional Sign," Journal of KIISE, vol. 42, no. 4 pp.511-521.
  4. Jung Y. S., Um K. J. and Won M. S.(2013), An Innovative Approach for Traffic Safety Improvement Based on Public Involvement via Social Network Services, KOTI, 2013-08.
  5. Kim A. R. and Cho S. B(2017), "A Fusion Method of Co-training and Label Propagation for Prediction of Bank Telemarketing," Journal of KIISE, vol. 44, no. 7, pp.686-691. https://doi.org/10.5626/JOK.2017.44.7.686
  6. Kim K. O., Moon Y. J., Lee J. D. and Cho S. A.(2016), The Korea Transport Institute, A Fundamental Research on Public Perceptions on Ethics, Legal, and Social Acceptance of Autonomous Vehicles(AV).
  7. Kim S. G., Cho H. K. and Kang J. Y.(2016), "The Status of Using Text Mining in Academic Research and Analysis Methods," Journal of Information Technology and Architecture, vol. 13. no. 2, pp.317-329.
  8. Lee B. J., Kim K. H. and Park J. I.(2015), Korea Research Institute for Human Settlements, Advanced Infrastructure Technologies and National Territorial Development -Focusing on Autonomous Vehicles-.
  9. Lee D. H., Kang H. G., Kim S. H. and Lee C. M.(2013), "Autocorrelation Analysis of the Sentiment with Stock Information Appearing on Big-Data," The Korean Journal of Financial Engineering, vol. 12, no. 2, pp.79-96.
  10. Lee G. H. and Lee K. J.(2013), "Twitter Sentiment Analysis for the Recent Trend Extracted from the Newspaper Article," Korea Information Processing Society, vol. 2, no. 10, pp.731-738.
  11. Oh C. S., Lee Y. T. and Ko M. S.(2016), "Establishment of ITS Policy Issues Investigation Method in the Road Section applied Text mining," Korea Institute of Intelligent Transport Systems, vol. 15, no. 6, pp.10-23. https://doi.org/10.12815/kits.2016.15.6.010
  12. Oh J. S.(2015), "Identifying Research Opportunities in the Convergence of Transportation and ICT Using Text Mining Techniques," Journal of Transportation Research, vol. 22, no. 4, pp.93-110.
  13. Yang M. H., Jung I. S., Kim Y. T. and Cho W. S.(2014), "An Awareness Identification and Preference Analysis for Domestic University Using SNS Data," The Korea Big Data Service Society, vol. 1, no. 1, pp.1-13. https://doi.org/10.29268/stbd.2014.1.1.1
  14. Yoon H. J.(2016), Implementation of the Sentiment Analysis Algorithm with Korean Twitter Data, Graduate School of Seoul National University of Science and Technology.

Cited by

  1. A Study on the Korean Ethical Guideline of Autonomous Vehicles vol.1, pp.132, 2017, https://doi.org/10.15801/je.1.132.201812.203
  2. Generating Traffic Safety Test Scenarios for Automated Vehicles using a Big Data Technique vol.23, pp.6, 2017, https://doi.org/10.1007/s12205-019-1287-4
  3. For Preventative Automated Driving System (PADS): Traffic Accident Context Analysis Based on Deep Neural Networks vol.9, pp.11, 2017, https://doi.org/10.3390/electronics9111829
  4. Defining Smart Mobility Service Levels via Text Mining vol.12, pp.21, 2017, https://doi.org/10.3390/su12219293