Research On Fitness App User Intention Model Based On Online Comments

In the wake of national policy advocacy and the impact of COVID-19,people’s health awareness is constantly enhanced,and fitness Apps that are not limited by time,space and geographical location emerge in an endless stream and quickly occupy an important position in the market.Fitness apps use Internet technology to assist users in real-time monitoring of exercise and provide a platform for information sharing and interaction,which is conducive to the implementation of the national fitness plan.However,fitness apps on the market have problems of function convergence and low data accuracy,which further affect users’willingness to use fitness apps.The number of active users of the fitness platform is an important starting point for the successful realization of the platform.At the same time,it is also an important prerequisite for the platform to integrate online and offline channels and form a closed loop of business including membership,course fees,advertising services,sports equipment sales and supporting venue sports.If the platform has no user,then the closed loop of the platform’s business will be empty.What factors will affect users’ willingness to use fitness platforms is an issue that enterprises should figure out.In the connected Internet age,it is common for people to post comments on a website platform,including comments about an event,a product or a service.There is a lot of valuable information hidden behind these online comments.However,the distribution of these comments is chaotic and fragmented,and manual collection,viewing and analysis will face a lot of difficulties and costs.Text mining technology can efficiently capture,calculate and analyze these comments,so as to obtain the key information in the comments,and then accurately analyze the main concerns and factors of users.Businesses can also design more targeted marketing programs based on this to promote their long-term development.Therefore,this paper uses text mining technology to mine online comments on the Keep platform,and preliminarily determines the factors affecting fitness App users’ willingness to use.Based on the theoretical basis of this paper and reference to existing research literature,a research model is established to further conduct empirical research on the constructed research model of willingness to use.Thus,it provides design or operation suggestions for fitness App enterprises on how to improve function design and increase user download rate and utilization rate.Firstly,preprocessing nearly 15,000 online comments about the Keep platform collected from seven Mai data network,using TF-IDF algorithm to obtain the top 500 high-value feature items,k-means clustering and word frequency analysis,and summarizing the factors affecting the use intention of fitness App users.Based on the theoretical basis of perceived value acceptance model,information system success theory and technology acceptance model,as well as existing research literature on fitness App users’willingness to use,e-health literacy was introduced to construct a research model of influencing factors of fitness App users’ willingness to use based on online reviews from the perspectives of platform and users.Secondly,the empirical analysis of this research model is further carried out,and the scale and questionnaire are designed.The data of pre-survey and formal survey are analyzed by using software SPSS26.0 and AMOS25.0,and the theoretical model and various hypotheses are tested.Finally,draw the research conclusion,and put forward practical and operable suggestions for the function optimization and operation of fitness apps.