Authors : Seong-Taek Park, Sung-Won Lee and Mi-Hyun Ko
Abstract: This research to analyze research trend on industry 4.0 through keyword network analysis and text mining techniques. Industry 4.0 articles were collected and an analysis was carried out using R, Rstudio, Tagxedo in this research. In order to analyze collected data, NLP package was used. After cleaning data, the number of frequency for important words was calculated. For key word network analysis, UCINET 6.0 was used in this research. Research on industry 4.0 is still in its initial stage but in this research documents were collected from Scopus an open access DB. These documents were used to grasp the trend of industry 4.0 by implementing text mining and network analysis which are big data techniques. Technologies, process and new turned out to be pretty high in in-degree in comparison to other key words. High in-degree indicates that it has strong power to absorb other key words. In contrast, industry, systems, production turned out to be relatively low in in-degree. Also when out-degree is examined, words such as industry, systems turned out to be high whereas words such as technologies, process turned out to below. This study is a study on the trend of industry 4.0. It provides a cornerstone for research on research support for industry 4.0.
Seong-Taek Park, Sung-Won Lee and Mi-Hyun Ko, 2018. Industry 4.0 on Keyword Network Analysis. Journal of Engineering and Applied Sciences, 13: 2442-2446.