동기∙위생 이론 기반 텍스트 마이닝 방법 활용 핀테크 이용자 만족 및 불만족 유발 요인 탐색 -토스(Toss) 사례를 중심으로-

Various innovative fintech services based on cutting-edge information and communications technologies (ICT) are emerging and have been the subject of increasing attention. In this context, this study aimed to investigate the reasons for the satisfaction or dissatisfaction of fintech service users through the use of text mining methodology. Online reviews relevant to 'Toss', which is one of the representative fintech services in the Google Play Store were collected by coding Python programs and using big data solutions. The collected data were analyzed using lexical analyses and Latent Dirichlet Allocation (LDA) topic modeling. The findings revealed that there were five factors related to satisfaction (free money transfer, various investment functions, various bank account management functions, convenience of usage, and advantageous point benefits) while six related to dissatisfaction (dissatisfaction with the functions of the pedometer, changes in the commission fee policy, errors and inconvenience after updates, issues with the functions of real estate investment products, problems in authentication methods, and account and card connection issues). The results of this study have value as a reference for the development of future marketing strategies and industrial policies for the fintech industry.