텍스트마이닝 및 감성분석에 의한 해양심층수에 대한 소비자 인식 분석

Abstract

The deep sea water (DSW) merchandise has been produced and commercialized after the “Development and management of deep sea water act (2007)” was enacted. Although various products have been manufactured and distributed to date, they seem to not reach the introduction stage of industry. To nurture DSW business into a full-fledged industry in the future, additionally treated deep sea water should be used to produce high quality and value-added products. Therefore, it is necessary to examine the customer satisfaction and to improve the quality of products. This study surveyed the products and reviews in several consumer communication platforms, such as internet websites and social networks (SNS), where ‧Drinkable Deep Sea Water‧ is a representative product. The purposes of survey were to identify the characteristics advantages and disadvantages of the merchandises and suggest the feasible ways to improve the products and services. To analyze the available data collected from review sites, text mining techniques such as TF / IDF, sentiment analysis, and network analysis were utilized. Customer reviews were crawled from online shopping malls and Naver blogs. Statistics and data mining, and graphics were analyzed and visualized using ‧R‧, Big Data Analysis ‧Textom‧, and Python that is an open source programming language based on C language. Through this study, it was able to understand the major issues on ‘Drinkable DSW’, and pros and cons of the products that are currently sold on the market. Furthermore, the strategical direction of product development and service improvement has been proposed from sentiment analysis.