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Online popular restaurants are those that are widely concerned by the society and sought after by the public through we media platform or internet marketing. Online comment is the product of the information age. The daily life of Internet users is to exchange information, express views and communicate with others through major Internet platforms. The outbreak of COVID-19 in 2020 has hit the catering industry in China. According to the statistics of the existing literature, it is found that there are few studies on online popular restaurants, and the research methods are relatively simple and traditional. The research on online comments of online popular restaurants can explore the emotional tendency of consumers, find the problems existing in online popular restaurants and put forward corresponding development suggestions. This paper uses Python technology to obtain the comments of 30 popular restaurants in Dalian on the public comment website, and puts forward corresponding opinions and suggestions on the operation of online popular restaurants through data mining. It is concluded that consumers care about the following aspects in the consumption process: taste, service, decoration style, waiting time in line. In this regard, we put forward the following suggestions: improve the taste of food, constantly push through the old and bring forth the new, and the primary task for the sustainable development of the restaurant is to ensure the taste; Improve service quality and create a high-quality service culture; Create a unique decoration style and resolutely resist and crack down on piracy; Reduce waiting time or provide better service during waiting time.
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