빅데이터를 활용한 e스포츠 인식 및 요구분석

Abstract

The purpose of this study is to analyze e-Sports keywords utilizing the big data analytical technique, and provide the basic data required for establishing e-Sports policies. To achieve this purpose of research, text mining, sentiment analysis, and CONCOR analysis were performed. The search volume analysis results for e-Sports keywords showed the maximum search volume as of October 2021. This period is the time of the 2021 LoL World Championships, and the success of the events has been shown to affect e-Sports interest. For keyword frequency analysis results, sports, games, Korea, competitions, athletes, league of legends, venues, battlegrounds, zenji, competitions were shown the highest frequency and derived as key keywords. As a result of sentiment analysis, the positive rate (75.81%) was found to be very high, and that was classified as good, recommendation, new, growth, best, wanted, etc. The negative rate was 24.19%, and negative keywords such as difficult, esoteric, caution, bad, etc. were classified. As a result of the CONCOR analysis, ‘National e-Sports League’, ‘e-Sports Professional Training’, ‘Asian Games’ and ‘Amateur e-Sports Events’ were formed as a group. These results are believed to reflect interests of demand for national and international e-Sports events and fostering the specialized workforce through the professional training courses.