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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

机译：基于Web Text Mining的旅游景区口碑促进 - 广东省万鹿谷的案例研究

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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.
机译：在互联网经济和共享经济的背景下，旅游景区应更加关注游客的网络舆论，并在培养网络中进行良好的工作。以广东省为例，为百度指数采取万路山谷生态旅游区，采用罗敦指数，并使用罗斯内容挖掘软件挖掘五个旅游网站的消费者评估文本，如桐城，携程，蚱蜢的蜂窝，美庭，喹啉等。通过挖掘旅游评估文本的高频特征词，构建社会语义网络矩阵地图，然后综合分析旅游网络关注指数和游客的评估感知信息，结果表明了景点的特点，服务态度和旅游设施是旅游评价的焦点：高频词数大，赞美程度高。因此，景区应注意“旅游+”行业的整合发展，提高服务质量，丰富旅游体验项目，促进生态旅游目的地的产业转型和更新和创新发展。

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