Principles, Approaches and Challenges of Applying Big Data in Safety Psychology Research - Kang, Liangguo; Wu, Chao; Wang, Bing (Frontiers in Psychology, 2019)
Big data is a well-known data processing technology in use today which widely applied to the integration of disciplines. Traditional methods of safety psychology are not well suitable to analyze psychological state, especially for manage human factors in industrial production. Also, big data is now a new way to excavate related insight by analyzing a large amount of psychological data. So, this paper is to propose the concept of big data of safety psychology (BDSP) and illustrate the challenge of big data in safety psychology. First, this paper is going to put forward the connotation of BDSP and analyze the difference between BDSP and sample data of safety psychology. Subsequently, this paper summarizes classification standard and basic characteristics of BDSP, then explore the framework of BDSP and construct the three-dimensional structures of BDSP. Lastly, this paper discusses the challenge of BDSP. This study was great help safety practitioner to solve psychological issue in safety domain, which point out one of the study trends of human factor in industrial safety.