User Sentiment Analysis Based on Online Reviews -Taking the Forbidden City Afternoon Tea Restaurant as an Example

Abstract

Nowadays, Internet consumption has become a familiar name, and there are more and more feedback channels on the production experience of consumers, and the content of evaluation also determines consumers' views on the goods to a certain extent. Therefore, the rational use of online comment contents can not only help consumers understand the basic information of products, but also help enterprises to better obtain the needs of consumers and provide more references for them. This paper selects the comment data of the Palace restaurant in Dianping software, and uses Python software to conduct data mining, emotion analysis, word frequency statistics and word cloud drawing. The conclusion shows that consumers have a positive emotional tendency towards the afternoon tea in the Palace Museum, with few negative comments. At the same time, consumers pay more attention to the dining location and food ingredients. Therefore, businesses can increase the improvement of dishes and environmental transformation through online reviews to better meet the needs of consumers. This research not only provides the basis for the evaluation of the business level, but also helps to enrich the consumer's understanding of the business.