Abstract
With the popularity of the Internet and the rapid development of mobile technology, e-commerce platforms have become one of the main channels for people's shopping and transactions. On e-commerce platforms, users' behavioral data are widely recorded and stored, which provides a rich data resource for studying user behavior. Studying data analysis of user behavior on e-commerce platforms helps to understand users' behavior patterns and provides a scientific basis for e-commerce platforms to optimize marketing strategies, improve user experience and realize personalized recommendations. The article elaborates on the data collection and processing work from three aspects: data source selection and acquisition, pre-processing and cleaning, data feature extraction and variable selection, and studies the user behavior of e-commerce platform from three perspectives: user purchasing behavior, user browsing behavior, and user commenting behavior, to promote the development and enhance the competitiveness of e-commerce platform.
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