Influence Mechanism And Empirical Study Of Online Consumers’ Emotional Fluctuation

With the continuous improvement of people’s consumption level,people’s quality of life has also improved.Therefore,the emotional experience of online consumers has become the focus of attention,and the direct basis for its measurement is the product review information published by consumers on the e-commerce platform.Through the review of previous studies,this paper clarifies the process of online consumer sentiment and the categories of influencing factors of consumer sentiment,and extracts four categories of factors as indicators for subsequent studies,namely,commodity attribute factors,logistics and service factors,product review factors,and commodity advertising factors.It is found that there is a positive correlation between factors and each factor has a positive effect on users’ emotions.The electric toothbrush reviews of the three brands of Jingdong Mall in 2021 are taken as the original corpus for empirical analysis.After preprocessing the noise data,Baidu intelligent cloud is called to score the comment text and distinguish the positive and negative categories of emotional polarity,which simplifies the quantitative means of discrimination.The word2 vec model is used to perform word segmentation analysis on the relevant comment text data,and the machine learning of text word vector is successfully realized,which makes a certain semantic correlation between the upper and lower words of the text.It is the new attempt of this semantic correlation that enables this paper to mine and reveal the real emotion of consumers from the comment text to a certain extent.According to the review time sequence to get the emotional value of the fluctuation curve,found that consumers on the three brands of emotional fluctuations have different trends,there are also differences.This is a new attempt that can further study the nature of consumer emotional change.The key words in the review text are extracted to obtain the influencing factors of consumers ’repurchase intention,and the linear discriminant analysis method is used to determine whether consumers will have repurchase behavior,so as to obtain consumers ’behavioral intention more simply and accurately.This is also a good inspiration for merchants,and based on the existing comments on online electric toothbrush,three emotion fluctuation control strategies are proposed.In terms of theoretical significance,this paper combines the questionnaire survey with the actual online reviews,and uses natural language processing technology and text sentiment analysis method to study consumer sentiment fluctuations,covering the online consumer group level and individual level,which ensures the scientific nature of the research to a certain extent and provides a reference for future research.In practical significance,the study of online consumer impact mechanism in this paper can better tap the key points that users care about products,understand user needs,and businesses can put forward solutions or improvement measures to improve consumer satisfaction,lock in purchased consumers,attract potential consumers,and expand market share.