Abstract
This paper proposed a novel approach to predict sales by analyzing the sentiment of online product reviews. The contributions of this paper are: (1) examine sentiment analysis to extract emotions such as anger, fear, or participation from the product reviews; (2) identified the time lag of the interaction between reviews and sale fluctuation; (3) applied three multiclass classification methods to forecast sales and combined them using a majority vote classifier for better performance and accuracy. Online sellers can utilize the proposed models to analyze the potential influence of reviews as an addition to traditional sale forecasting methods.
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