Semantic Analysis of Transportation Related Researches

Abstract

The purpose of this study is to analyze the research trends of traffic research through analyzing the semantic network of existing traffic related research papers and to compare research trends in Korea. The subjects of the analysis are about 21,000 research papers collected from the database of 'Web of Science' which is an academic information database. Using the open source software, Khcoder, semantic network analysis was carried out with meta information such as theses, abstracts, research fields. As a result of the analysis, major research areas were divided into traffic model and analysis, energy efficiency, vehicle, and mobile behavior. As a result of analyzing the major research changes by period, researches focused on reducing the use of fossil fuels before and after the 1992 Climate Change Convention have increased intensively. This can explain that the policy has a great influence on the flow of research. From 1970 to 1996, there were 9772 research articles in the United States and 456 research articles in Korea. Results of the semantic network analysis The United States and Korea show similar network patterns despite differences in terms such as history, geography, economic power, and population. However, the difference between Korea and the United States is that research on public transport such as buses and transportation is being carried out steadily. This explains that Korean transportation research and policy accepts American academic theory as it is, but it shows that public transportation research should be continuously carried out in accordance with the situation of Korea where population is small and population is concentrated in city. Quantitative and objective analysis methods need to be developed to objectively analyze advanced European transport policies and research trends promoting public transport policies for the above reasons. Therefore, this study is meaningful because it tried to analyze research trend through quantitative analysis method called semantic network analysis.