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A Study on the Effects of Online Word-of-Mouth on Game Consumers Based on Sentimental Analysis

감성분석 기반의 게임 소비자 온라인 구전효과 연구

  • 정근웅 (성균관대학교 일반대학원 경영학과) ;
  • 김종욱 (성균관대학교 경영전문대학원)
  • Received : 2017.12.22
  • Accepted : 2018.03.20
  • Published : 2018.03.28

Abstract

Unlike the past, when distributors distributed games through retail stores, they are now selling digital content, which is based on online distribution channels. This study analyzes the effects of eWOM (electronic Word of Mouth) on sales volume of game sold on Steam, an online digital content distribution channel. Recently, data mining techniques based on Big Data have been studied. In this study, emotion index of eWOM is derived by emotional analysis which is a text mining technique that can analyze the emotion of each review among factors of eWOM. Emotional analysis utilizes Naive Bayes and SVM classifier and calculates the emotion index through the SVM classifier with high accuracy. Regression analysis is performed on the dependent variable, sales variation, using the emotion index, the number of reviews of each game, the size of eWOM, and the user score of each game, which is a rating of eWOM. Regression analysis revealed that the size of the independent variable eWOM and the emotion index of the eWOM were influential on the dependent variable, sales variation. This study suggests the factors of eWOM that affect the sales volume when Korean game companies enter overseas markets based on steam.

Keywords

eWOM;Text Mining;Sentimental Analysis;Opinion Mining;Machine Learning

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