The Impact of Word Volume, Text Sentiment, Sentiment Entropy and Structure in eWOM on Product Sales Performance – The Case of Motion Picture Industry

• Main Authors: Meng-Hsuan Wu, 吳孟璇
• Other Authors: Lichung Ren
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/4z6skd

碩士 === 國立臺灣大學 === 國際企業學研究所 === 104 === A lot has been studied in the influences of WOM volume and valence on box office revenues by applying online review quantities and ratings. However, little is known about the force of the quantities and sentiments of words in WOM. This research is conducted to explore the force of words in WOM. With text mining and sentiment analysis techniques, the study is to examine the explanatory power of words to box office performances by word volumes, sentiment scores, and sentiment structures of words, including the entropy and the composition. The study compares the effects of words and of the classical review volume and valence without involving other variables of the movies. The result indicates that the volume and valence of words can substitute, or even surpass, those of reviews by both higher significant level and stronger explanatory power. In addition, the study has found that the entropy of text sentiment (score clusters) has negative effects on box office performances. Specifically, the decrease in the ratios of certain negative or positive word clusters, along with the increase in the ratios of certain negative or positive word clusters, collaboratively generate a positive synergy on box office performances.