Application Research Of Text Mining In Online Shopping User Reviews

In the era of information generated value,information has become the main trends of times development.In daily life,a large amount of information is generated every second of the day,and people tend to consolidate related information on the internet for decision-making.A variety of information acquisition and mining technologies as ansupplementary means to evolve.At the same time,the rapid development of Internet technology has also brought about tremendous changes in our lives.Under the age background,online shopping that has been risen in recent years and is growing up rapidly has become a part of people’s daily life.With the gradual expansion of the number of online shoppers,the scale of online shopping reviews is also expanding.therefore,it’s even more difficult to get effective information in such a large online shopping review.However,the emergence of text mining has provided a solution to this problem.This paper uses text mining technology to crawling and analyze the reviews data of different E-Commerce platforms about Huawei mate9 in order to obtain different E-Commerce platforms online shoppers’ concerns and needs for the product,and the corresponding attitude.On the one hand,it can help online shoppers understand the commodity information from multiple dimensions,and make purchase decisions;on the other hand,it can also help businesses understand purchase demands of online shoppers,and fing out quality or sales problems of smart-phone,and then optimize the subsequent products and services for making it more humane.The research work of this paper is mainly divided into four parts.The first part uses GooSeeker to crawling user reviews on Huawei mate9 from Tmall,Jingdong and Vmall.The second part is data pre-processing work,including using jieba algorithm to segment the comment data,and adopting different stop word strategies to meet the requirements of different analysis,and then building Character-Words list by regular expression.The third part mainly undertakes a semantic mining on building word cloud and topic model for comment data from the dimension of e-commerce platform;the fourth mainly makes part sentiment analysis of user reviews on two dimensions of e-commerce platform and mobile phone features.The final analysis results show that from a E-Commerce platform perspective,Vmall users have a greater sense of belonging and loyalty,and more concerned about the social value of Huawei brand,and Tmall users are more concerned about performance-price ratio and shopping experience,and Jingdong users’ focus is on the performance of mobile phones.Starting from the angle of feature attribute,the screen size,cost,logistics and sound quality still has much room for improvement,especially the screen size and cost-effective.The Huawei mate9 is doing well and has been widely recognized by users in appearance design,screen resolution,handle and custom service.