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Under the background of Internet economy and sharing economy, tourist scenic spots should pay more attention to tourists' network public opinion and do a good job in cultivating network word of mouth. Taking Wanlu Valley ecotourism area in Guangdong province as an example, the paper collects Baidu index and uses ROST Content Mining software to excavate the post-consumer evaluation text of five tourist websites, such as Tongcheng, Ctrip, Grasshopper's Honeycomb, Meituan, Qunar, etc. By mining the high-frequency characteristic words of the tourist evaluation text, constructing the social semantic network matrix map, and then synthetically analyzing the tourist network attention index and the tourists' evaluation perception information, the result demonstrate that the characteristics of scenic spots, service attitude and tourist facilities are the focuses of tourist evaluation: the number of high-frequency words is large and the degree of praise is high. Therefore, the scenic spots should pay attention to the integration development of "tourism +" industry, improve service quality, enrich tourism experience projects, promote the industrial transformation and update and innovation development of eco-tourism destination.

Research on the Promotion of Word of Mouth in Tourist Scenic Spots Based on Web Text Mining——the Case Study of Wanlu Valley in Guangdong Province