基于文本挖掘的在线旅游热词情报分析——以携程网为例

An Information Analysis of the Hot Words of Online Travel Based on Text Mining

文章利用网络爬虫软件抽取携程网在线旅游文本内容,利用内容分析法对所得样本进行热词分析、共词分析和长尾分析,获得游客在线旅游情报决策的一系列行为规律。实证研究结果表明游客在线旅游决策中对景点的感知强于对地域的感知,对地域的感知强于对旅游方式的感知;旅游服务提供商需要加大对小众旅游产品的开发,避免同质化竞争;旅游服务体验反馈已经成为游客在线旅游决策的重要依据。

This paper uses web crawler to extract the content of online travel text,and uses the content analysis method to carry out hot words analysis,co-word analysis and long tail analysis of the obtained samples. On this basis,the paper discovers a series of behavioral patterns of tourists＇ online travel information decision. The results of empirical research show that the perception of scenic spots in tourists＇ travel decision is stronger than that of the region,and the perception of the area is stronger than that of the travel mode. The tourism service providers need to increase the development of the niche tourist products and avoid homogeneity competition. Tourism service experience feedback has become an important basis for tourists to make online travel decisions.