Journal of the Korean Society of Safety (한국안전학회지)

The Korean Society of Safety (한국안전학회)
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Data Analytics for Social Risk Forecasting and Assessment of New Technology

데이터 분석 기반 미래 신기술의 사회적 위험 예측과 위험성 평가

  • Suh, Yongyoon (Department of Safety Engineering, Pukyong National University)
  • Received : 2017.02.09
  • Accepted : 2017.05.31
  • Published : 2017.06.30
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Abstract

A new technology has provided the nation, industry, society, and people with innovative and useful functions. National economy and society has been improved through this technology innovation. Despite the benefit of technology innovation, however, since technology society was sufficiently mature, the unintended side effect and negative impact of new technology on society and human beings has been highlighted. Thus, it is important to investigate a risk of new technology for the future society. Recently, the risks of the new technology are being suggested through a large amount of social data such as news articles and report contents. These data can be used as effective sources for quantitatively and systematically forecasting social risks of new technology. In this respect, this paper aims to propose a data-driven process for forecasting and assessing social risks of future new technology using the text mining, 4M(Man, Machine, Media, and Management) framework, and analytic hierarchy process (AHP). First, social risk factors are forecasted based on social risk keywords extracted by the text mining of documents containing social risk information of new technology. Second, the social risk keywords are classified into the 4M causes to identify the degree of risk causes. Finally, the AHP is applied to assess impact of social risk factors and 4M causes based on social risk keywords. The proposed approach is helpful for technology engineers, safety managers, and policy makers to consider social risks of new technology and their impact.

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