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http://dx.doi.org/10.14400/JDC.2022.20.3.131

Trend Analysis of FinTech and Digital Financial Services using Text Mining  

Kim, Do-Hee (Dept. of Big Data Analysis Convergence, Sookmyung Women's University)
Kim, Min-Jeong (Dept. of Consumer Economics, Sookmyung Women's University)
Publication Information
Journal of Digital Convergence / v.20, no.3, 2022 , pp. 131-143 More about this Journal
Abstract
Focusing on FinTech keywords, this study is analyzing newspaper articles and Twitter data by using text mining methodology in order to understand trends in the industry of domestic digital financial service. In the growth of FinTech lifecycle, the frequency analysis has been performed by four important points: Mobile Payment Service, Internet Primary Bank, Data 3 Act, MyData Businesses. Utilizing frequency analysis, which combines the keywords 'China', 'USA', and 'Future' with the 'FinTech', has been predicting the FinTech industry regarding of the current and future position. Next, sentiment analysis was conducted on Twitter to quantify consumers' expectations and concerns about FinTech services. Therefore, this study is able to share meaningful perspective in that it presented strategic directions that the government and companies can use to understanding future FinTech market by combining frequency analysis and sentiment analysis.
Keywords
FinTech; Finance; Text Mining; Frequency Analysis; Sentiment Analysis;
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Times Cited By KSCI : 8  (Citation Analysis)
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