Text Mining Analysis on Robot and Logistics: Employing NAVER News Article Big Data

This research aims to highlight issues related to logistics and robot applying a text mining technique to Naver news article big data at the time of paying much attention to AI and big data technology as well as agenda on fourth industrial revolution. In ordr to analyze the role of robots in the logistics industry, this study employed 609 NAVER news articles from January 21, 2020 to December 31, 2020 for the analysis, excluding redundant and irrelevant articles. News article frequency analysis, news article keyworkd analysis, cosine similarity and co-occurence frequency analysis were conducted for the visualization of the research findings employing R program in order to invegstigate into the main issues related to news articles.. Cosine similarity and co-occurrence frequency as well as wordcloud analysis was visualized. It was found that the the news articles dealing with robots and logistics addressed the subjects related to corporations, robot, technology, and logistics together, presenting these keywords in the ranking of keyword frequency from the various perspectives. It is suggested that specific projects on delivery of products/services in an efficent manner needs to be initiated in order to apply the technology of robotics to not only the logistics industry, but also service industry (e.g., hotel and tourism-related businesses). This study has contributed to the presentation of the issue on robot among the fourth industrial revolution technologies.