Statistical Analysis Of Customer Satisfaction Of Footwear Products Based On Online Reviews

In recent years,with the rapid development of computer technology,Web2.0technology and content have made great progress,and the concept of "user-centred" has gradually been accepted by the public.This trend has made more and more information available on the Internet,and its importance has also increased.Under the background of the new development pattern of "taking domestic circulation as the main body and domestic and international double circulation promoting each other",rooted in the capacity and potential of China’s domestic market,focusing on the strong foundation and strength of "made in China",the proposal of the new development pattern gives a large number of domestic brands a larger development platform and brings more development opportunities.In this paper,Python crawler technology is used to crawl the online review texts of several products of basketball shoes,running shoes and leisure shoes under the main brand of ’ Anta ’ on Jingdong platform as of June 3,2022,and preprocess the crawled data.The word cloud map is used to visually display the specific distribution of high-frequency words in the online review text of the product,and the ’ word co-occurrence ’ text network diagram is used to analyze the relationship contained in the high-frequency words under each category.According to the LDA text topic modeling principle,the online review text of the product is modeled,and the model is continuously trained.Based on the criteria of less confusion and large discrimination of topic word distribution,three topics are extracted from the online review text of the three major categories,and the corresponding topic keywords under each topic are output to obtain the topic attribution of each review text.The snow NLP algorithm is used to calculate the sentiment score of each online review text.At the same time,the weight of each keyword is calculated according to the principle of Tf-idf algorithm,and the sentiment score of each category and the corresponding topic under each category are calculated.From the research results,consumers’ concerns have something in common,which is reflected in the workmanship of the product and the shoe last part.At the same time,due to the different characteristics of the product,for basketball shoes,consumers also pay attention to the bottom of basketball shoes;running shoes are in the unexpected bottom part,and leisure shoes pay more attention to the upper part of the product.The research on customer satisfaction of goods has been cultivated by many scholars for many years,but the research on footwear is relatively scarce.This paper draws on the research results of other categories of goods,uses text mining to avoid the subjective uncertainty of using traditional scales,and outputs visual research results that are clear and easy to understand.This paper aims to provide feasible and scientific reference suggestions for manufacturers,consumers and the market to promote a virtuous circle of the market.