ABSTRACT
With the rapid development of the Internet, the e-commerce industry has become more and more popular, resulting in a large number of commodity review data, which provides users with reference value. However, the amount of comment data on the network is often huge, and it is difficult for consumers to extract useful information from these mixed opinions. Ther efore, how to effectively analyze the product comment data and extract the user’s emotion is the key issue at this stage. This paper proposes a comprehensive evaluation of online stores based on user sentiment analysis, which can accurately identify the evaluation of users on online shopping goods, point out the emotional trend of users, provide reference information for other users, and provide feedback information for businesses. As a reference index for e-commerce website to use recommendation algorithm for personalized recommendation.
