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《Resource Development & Market》 2017-01
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Comparative Research on Travel Sharing of Typical Travel Website Based on Text Mining——Taking Gansu Province as an Example

WANG Yao-bin;YANG Ling;SUN Chuan-ling;JIANG Jin-ping;Tourism College,Northwest Normal University;  
As a new field of tourism research,travel sharing attracted the attention of many experts and scholars in China and aboard. Selected Taking Sconic Spots Gansu Province as an example,the ctrip,mafengwo,lvmama and tuniu travel websites were as research sample,using the text mining method to analyze the word frequency,emotion and semantic website. The results showed that tourists were most concerned with the characterization of typical tourist signs and at the core of tourism resources of the natural and humanistic attractions,especially in the humanities was the most typical. From the perspective of emotion type,positive emotion dominated in emotional components,negative emotion accounted for a small proportion. As a tourist destination,Gansu Province had a high tourism attraction to tourist. But the negative factors that affected the emotion of tourists,such as infrastructure lag,traffic congestion and ticket price were too high which could not be ignored. Furthermore,more than half of the scenic spots or tourist attractions had no power for resources. Finally,the centrality of semantic website of scenic spots was low and structure of semantic website was relatively loose,so there was no factionalism and small group phenomenon.In addition,in the same subgroup of the various attractions were not connect too good. To same extent,the huddle phenomenon was difficult to appear,and it also reflected the connect between the various attractions in Gansu Province which was very seldom. Therefore,it was particularly important to strengthen the communication and cooperation among the attractions in Gansu Province.
【Fund】: 国家自然科学基金项目“粗糙集与模糊集结合的民族地区乡村旅游扶贫精准识别研究”(编号:41661107);; 国家旅游局旅游业青年专家培养计划项目“主客双重感知视角的民族地区旅游影响模型构建与实证”(编号:TYEPT201453);; 西北师范大学人文社科骨干项目(编号:SKGG14024)
【CateGory Index】: F592.7
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