Browse > Article
http://dx.doi.org/10.12815/kits.2017.16.6.231

Analysis of the Perception of Autonomous Vehicles Using Text Mining Technique  

Im, I-Jeong (Dept. of Urban Planning, Univ. of Hongik)
Song, Jae-In (Dept. of Urban Planning, Univ. of Hongik)
Lee, Ja-Young (Dept. of Urban Planning, Univ. of Hongik)
Hwang, Kee-Yeon (Dept. of Urban Planning, Univ. of Hongik)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.16, no.6, 2017 , pp. 231-243 More about this Journal
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.
Keywords
Autonomous Vehicle; Analysis of Perception; Text mining; Emotional Analysis; Social Acceptance;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
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.   DOI
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.   DOI
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.   DOI
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.