A Study on User Perception of Delivery Apps Using Text Mining Techniques : Focusing on Coupang Eats App Reviews

• 영문명: A Study on User Perception of Delivery Apps Using Text Mining Techniques : Focusing on Coupang Eats App Reviews
• 발행기관: 위기관리 이론과 실천
• 저자명: 이승민(Seungmin Lee) 강원석(Wonseok Kang) 김현호(Hyunho Kim)
• 간행물 정보: 『JSCM(Journal of Safety and Crisis Management)』Vol.14 No.5, 15~28쪽, 전체 14쪽
• 주제분류: 사회과학 > 행정학
• 파일형태: PDF
• 발행일자: 2024.05.30

국문 초록

The purpose of this study is to identify users' perceptions of the Coupang Eats app, which is maintaining growth in the delivery app market, and to derive improvements by identifying factors that induce and strengthen positive/negative perceptions. As a result of the study, first, the frequency and connection centrality of the word 'fast' were high, indicating that the speed of the Coupang Eats service is receiving a lot of attention. Second, as a result of CONCOR analysis, the areas of interest of users were identified by clustering the main keywords of the Coupang Eats app review data and dividing them into groups. A total of four groups could be identified: 'benefit service', 'satisfaction', 'inconvenience', and 'other', indicating the areas of interest of users. Third, through emotional vocabulary analysis, it was confirmed that there were more positive vocabulary than negative vocabulary in the Coupang Eats app review data. Fourth, the result of document sensitivity classification also confirmed that positive reviews appeared more than negative reviews. Finally, a text analysis was conducted on positive and negative reviews classified according to the document sensitivity classification to derive factors that induce and strengthen positive and negative perceptions.

목차

Introduction

Theoretical Background

Research Method

Research Results and Discussion

Conclusion

Acknowledgement

References

키워드

delivery app user recognition text mining sentiment analysis big data analysis TEXTOM