A Study Of Online Review And Its Impact On Commodity Prices

With the popularity of the Internet and rapid development of e-commerce, online shopping has become an important part of daily shopping. The China Online shopping market Report shows that online reviews is the critical factor of online shopping decisions nowadays and 37.5 percent of online shoppers mainly consider online reviews when buying unfamiliar products. The second is the website visibility and reputation. The propensity of online reviews will influence consumers' purchase decisions andthe demand of goods, then eventually affect the profits of enterprises. The emotional tendency of product reviews is one of the main reasons that affecting other consumers' purchase decisions. So the e-retailing and B2 C enterprises' pricing strategy can no longer use the traditional ways, they must consider the impact of reviews on pricing.The paper will analyze the content of online reviews as the phenomenon that more and more users rely on the online reviews to decide whether to buy a commodity, and the main work is to find the correlation between the emotional tendencies of review text and commodity price. The purpose of the study is to find out the contents of online reviews and its impact on commodity pricing. The paper conducted a literature review of relevant theory such as online reviews, logistics reviews and pricing strategy, and put forward the hypothesis that the content of consumers reviews are influenced by membership levels and that the rate of positive reviews is correlated with product price, and also propose a conceptual model.The reviews data in recent months of washing machine on the JD.com are used to analyze the distribution of membership levels, comments intervals, positive rates and other content. Through establishing a training set, we use machine learning languages to analysis the emotional of reviews, When compares to the favorable rate given by the shopping site, we find that they are very different. After the analysis of the data, it shows that the higher level of membership tends to give positive comments, and the lower ones are in the contrast. Based on the above analysis, the focal point is a correlation analysis of positive rates and the changes of price, mainly studied the delay impact of positive rates on price. Finally, after research the 20 machines' reviews in JD.com, we found that half of the machines' price have correlation with online reviews, while 30 percent machines' price have no significant changes in six months.The data of this study including commodity prices, the level of comments, comment date, date of purchase, experiences and score of goods, then conduct data mining and analysis the relationship between different elements with scientific methods. Online reviews is an important part of among consumers and sellers, and also as a module of a page, it is of great importance to extract useful data from a large number of reviews to understand the relation in it and promote the healthy development of e-commerce. Then the methods of the research can be extended to the study of similar products, the conclusion can be referred by commercial enterprises for pricing and help other consumers shopping online to make decision.