Information Extracting and Analysis on Safe Operation of Online Car-hailing Based on Text Mining: The Case of China

The recent rise of online car-hailing has successfully promoted the booming of sharing economy in transportation and sets up new mode for intra-city trips. However, it comes with serious risk for passengers, drivers and online car-hailing platforms (OCPs). Few researches have explored the risk of OCPs services despite most research focus on the safe assessment/evaluation system. As a special transportation service enterprise, the research on the safe of OCPs is obviously insufficient. This paper explores the focus of online car Hailing industry-related researches, and build a framework for OCPs services by identifying 8 topics from 883 research papers. Natural language processing method are adopted to achieve the target and specifically, the TF-IDF algorithm and LDA model are applied in the study. The results show that regional policy background provides basic safe situation for OCPs services, and stress the importance of safety improvement from both macro vision and detailed optimization method. Besides, current disputes and dilemma of OCPs safe operation and the legal status and responsibility of OCPs should be paid more attention. In addition, shielded from various risks (e.g., functional risk, time risk physical risk, financial risk) is a key to get the advantage in the competition for market share. Finally, practice and planning of OCPs services in regions is needed to promote the safe operation of OCPs services.