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Article

Analysis of Marine Safety Impacts Using Social Big Data in Marine Transportation

해상교통 소셜 빅데이터를 활용한 해양안전 영향도 분석

Jae-Min JANG1
,
Eubong LEE2
,
Ho-Yong JUNG3*
장 재민1
,
이 유봉2
,
정 호용3*
1Ph.D Course, Graduate School of Environmental Studies, Seoul National University, Seoul 08826, Korea
2Senior Research Fellow, Korea Legislation Research Institute, Sejong 30147, Korea
3Ph.D Course, Graduate School of Economic & Statistics, Korea University Sejong Campus, Sejong 30019, Korea
1서울대학교 환경대학원 환경계획과 박사수료
2한국법제연구원 법제조사평가연구실 연구위원
3고려대학교 경제통계학과 박사수료
* Corresponding Author
30 April 2019. pp. 148-167
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Abstract

In the wake of the Sewol ferry disaster, the government has set up various safety measures for maritime safety, but the number of accidents seems to have increased. Over time, the traffic accidents have shown the new and complex. The maritime safety policy should take into account these various and complex characteristics. This study analyzed the impact of marine safety based on social data that well reflects the characteristics of the period and can be combined with various factors. The analysis method collected materials related to marine safety based on the social data in order to construct the population, and conducted the grouping analysis and influence analysis through key word analysis. For the monthly analysis, the influential variables using SPSS were derived based on the words that appeared continuously throughout the year. From the analysis results, this studies explored the factors affecting maritime safety and its policy implications. According to the analysis, different characteristics of marine accidents were derived based on the size of ships, linetype, weather, accident type, accident cause, accident area, and structural institution. Therefore, it seems necessary to draw up measures based on these analysis results in order to set up policy measures that reflect the reality. In addition, it is necessary to check that the Basic Traffic Safety Plan established by the government contains sufficient analysis of key words and accident characteristics analyzed in this study. In particular, it is necessary to review whether safety measures for marine safety are being discussed sufficiently among ordinary citizens or whether maritime safety-related risk factors and countermeasures are fully known to ordinary citizens. As the results of this study are based on associated searched terms, there are difficulties as a direct policy alternative, but there remains various possibilities for later studies to be applied mixed with quantitative data analysis.

Keywords
impact analysis
keyword analysis
marine safety
regression analysis,
social data

정부는 세월호 참사를 계기로 해양안전을 위해 다양한 안전대책을 수립하였으나 사고발생건수는 증가된 것으로 보인다. 교통사고는 시간이 흐를수록 신종사고 및 복합유형의 형태가 높은 만큼 이러한 특성이 고려되어야 한다. 본 연구는 시대적 특성이 잘 반영되고, 다양한 요인과 결합이 가능한 Social Data를 기반으로 해양안전의 영향도를 분석하였다. 분석방법은 모집단을 구성하기 위해 Social Data를 기반으로 해양안전과 관련된 내용을 수집하였으며, key word 분석을 통해 그룹핑 분석 및 영향도 분석을 시행하였다. 월별분석은 SPSS를 활용하여 한 해 동안 지속적으로 도출되는 단어를 기준으로 영향변수를 도출하였고, 분석결과를 통해 해양안전의 영향요인 탐색 및 활용방안을 제시하였다. 분석결과 선박규모별, 선종별, 기상별, 사고유형별, 사고원인별, 발생지역별, 구조기관별을 중심으로 해양안전의 영향도는 상이한 특성이 도출되었다. 따라서 현실에 적합한 안전사고 개선방안 마련을 위하여는 이러한 결과를 기반으로 대책 마련이 필요한 것으로 보인다. 이외에도 정부에서 수립 중인 교통안전 기본계회 등이 본 연구에서 분석된 주요단어 및 사고특성 분석 내용이 충분히 담겨 있는지 점검도 필요할 것이다. 특히 해양안전에 대한 안전대책이 일반시민들 사이에서 충분히 논의되고 있는지 또는 일반시민들에게 해양안전 관련 위험요인과 대처방안이 충분히 알려지고 있는지 점검이 필요하다. 본 연구 결과는 연관 검색어를 기반으로 영향도를 분석한 만큼 직접적인 대안책으로 다소 무리가 존재하나 추후 정량적 데이터와 융합을 통해 사용된다면 보다 적용가능성이 높아질 것이다.

키워드
영향도 분석
키워드분석
해양안전
회귀분석
소셜 데이터
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Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 37
  • No :2
  • Pages :148-167
  • Received Date : 2019-01-17
  • Revised Date : 2019-02-15
  • Accepted Date : 2019-03-30
  • DOI :https://doi.org/10.7470/jkst.2019.37.2.148
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