Research On The Consumer Online Reviews Under Different E-commerce Modes

With the rapid development of the Internet,e-commerce is also developing rapidly.Different from the phenomenon that consumers are the receivers of information in the past,more and more people can express their shopping and using experience of products with the help of e-commerce platform.In this era,a large number of ecommerce transactions have generated a large number of online consumer evaluations,which cover consumers' comprehensive feedback on goods,logistics,services and other aspects.Based on these feedback,businesses can develop targeted marketing strategies and product research and development plans by tapping consumers' emotional tendencies towards different features of products.Through online evaluation,consumers can understand the use experience of existing buyers on various features of products,and make purchase decisions according to their own needs to reduce purchase risks.In this paper,on the basis of carding the research status at home and abroad,using text mining methods to analyze consumer online evaluation,mainly from the different modes of electricity consumers online evaluation features,consumers online product life cycle assessment to study the two aspects,in order to provide help for consumers and businesses to make decisions.The details are as follows:Based on the characteristics of fast upgrading of mobile phone products,strong competition among different products,clear product features and hard to lack in daily life,taking Huawei Mate20 Pro mobile phone as the research object,and aiming at the problem of whether there are differences in consumers' online evaluation under different e-commerce modes,Based on the existing research,the e-commerce model is divided into wholesale model,consignment model and wholesale-consignment model,and the differences of consumers' online evaluation under different e-commerce models are analyzed through text mining,association analysis and other methods.Based on the product life cycle theory,K-means clustering and sentiment analysis are used to analyze the characteristic differences of consumers' online evaluations in different product life cycles under different e-commerce modes.The results show that there are indeed differences in consumers' online evaluation among different e-commerce models,and the use of such differences can better provide decision-making help for different consumer groups and businesses.In this paper,the online evaluation of different e-commerce modes and different product life cycles is studied from the perspective of feature keywords,and different types of online evaluation are compared.The problem of relatively coarse research granularity is improved,and a new idea of online evaluation feature research is provided.In terms of practical significance,it can help consumers and businesses choose suitable online evaluations for reference based on their own needs,and provide a basis for businesses to make marketing decisions and product research and development plans.