游客对国家中心城市5A级景区空气质量的情感分析

The sentiment analysis of air quality in 5A scenic spots in national central cities

国家中心城市是区域发展的“领头羊”,分析游客对国家中心城市空气质量的感知对旅游者行为选择和旅游地形象建构具有重要意义。采用网络爬虫技术获取2011年1月~2018年12月游客在新浪微博发布的关于中国232个5A景区有关空气质量的36737条评论,以Python编程调用Boson平台上面向中文社交媒体数据的人工神经网络这一机器学习方法测算篇章文本的情感值为基础,从景区、城市以及中心城市在全国中的位置三个层面分析游客对国家中心城市空气质量的情感值。研究发现:①游客对国家中心城市的情感倾向以正面为主,城市间情感倾向性差异较小,情感值随时间推移呈缓慢波动上升趋势,空间上呈现出的“东低西高、北低南高”特点与现实状况较为吻合。②九大中心城市游客对空气质量风险感知普遍较低。③情感值与景区类型具有相关性,且自然型景区较明显高于人文型景区。该研究丰富了旅游者情感研究的内涵,拓展了情感分析在旅游研究中的应用深度,对城市旅游空气环境的改善具有一定的指导作用。

National central cities are the "leader" of regional development.To analyze tourists’ perceptions of air quality of national central cities is of great significance to the choice of tourists’ behavior and the construction of tourist destination imagine.With web crawler technology, we obtained 36737 comments on air quality of 232 China’s 5 A scenic spots posted by tourists on Sina Weibo from January 2011 to December 2018.Based on the sentiment orientation of the tourists, we analyzed and calculated data using the method of machine learning, which accessed data from Chinese social media with Python and Boson.We analyzed the sentiment orientation of the tourists of the air quality of national central cities from three levels-scenic area, cities and the location of central cites, and further explained the reasons behind using content analysis.It is found that:(1)The sentiment orientation of tourists to the national central city is mainly positive, the gap is relatively small, and affective values showed a slow and fluctuating upward trend over time.In space, the characteristics of "high in the west and low in the east, high in the south and low in the north" is consistent with the layout of the national urban air pollution.(2)Tourists in the nine central cities generally have a low perception of air quality.(3)The sentiment orientation of tourists has correlation with the type of scenic spots, and the emotional value of natural landscape scenic spots is higher than that of human landscape scenic spots.This research enriches the connotation of tourist emotion research, expands the application depth of emotion analysis in tourism research, and plays a certain guiding role for the improvement of urban tourism air environment.