| In recent years,online shopping has become an indispensable way of consumption in life,but due to the virtual nature of the network,consumers cannot truly touch and evaluate the goods or services sold by the merchants.Therefore,online reviews have become a key factor on consumers' purchasing intention.Consumers get information from online reviews that cannot be obtained from product descriptions,eliminating information asymmetry and purchase uncertainty in online shopping.However,due to the rapid development of online shopping,the number of online reviews has begun to increase rapidly,and it takes a lot of time and effort for consumers to obtain useful information from online reviews.Therefore,how to accurately identify useful comments has become a concern of scholars.At present,its main research focuses on review ratings,review information,and review emotions.Review information and review emotions are two factors that are highly valued.However,measuring the review information from the perspective of information entropy,and describing the influence of emotion on the review helpfulness and the influence on the perception of information by using the emotion polarity and the total amount of emotion,is a new perspective to identify the review helpfulness.Based on the previous related research,combined with the concept and characteristics of information entropy and emotion,this paper sorts out the relationship logic between the review helpfulness,information entropy,emotion polarity and the total amount of emotion,and proposes a relationship between the four factors.By crawling the Ebay product and review information,we obtained data of two different types of products,such as action movies and iphone,a total of 6,437 samples,each sample contains product price,product score,comment score,comment text and other information.The information entropy,emotion polarity,and the total amount of emotion of the reviews were calculated using NLTK and SentiStrength software.Finally,descriptive statistics and regression analysis were performed on the data using STATA14.0 software.The empirical results show that in the experient products,information entropy,emotion polarity and the total amount of emotion have a significant positive impact on the review helpfulness.The total amount of emotion plays a positive role in the relationship between information entropy and review helpfulness.In search products,information entropy has a significant negative impact on the usefulness of comments.Emotional polarity and the total amount of emotional have a significant positive impact on the review helpfulness,and the total amount of emotion and emotion polarity play a positive role on the relationship of information entropy and review helpfulness.The total amount of emotion and emotion polarity play a greater role in experient products than search products.Based on the conclusions of this paper,we propose corresponding recommendations to help companies manage.The e-commerce platform should improve the ranking mechanism of online reviews,and can effectively identify useful reviews by commenting on factors such as information entropy,emotion polarity and the total amount of emotion,and present them for consumers to browse.Merchants should treat different types of product information differently,and encourage consumers to add appropriate emotional descriptions when reviewing products.Online businesses don't have to be too afraid of negative comments,too much attention to the polarity of comments.Positive comments increase the usefulness of comments and enhance consumer perceptions of comment,while excessively negative comments are not very useful.This study supplements the relevant research on the review helpfulness,and also provides an in-depth interpretation of the impact of the review helpfulness,allowing e-commerce platforms and businesses to understand the relationship between review information and review emotions.The corresponding management measures are taken. |
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