Resources Science ›› 2018, Vol. 40 ›› Issue (7): 1483-1493.doi: 10.18402/resci.2018.07.16

• Orginal Article • Previous Articles    

A research on destination image and perceived dimension difference based on big data of tourists’ comments: a case of Nanjing

Feifei XU1(), Liqing LA1(), Feng YE2   

  1. 1. Tourism Department, School of Humanities, Southeast University, Nanjing 210096, China
    2. Hospitality and Tourism Management, Purdue University, West Lafayette 47906, U. S
  • Received:2017-11-15 Revised:2018-02-08 Online:2018-07-20 Published:2018-07-20

Abstract:

With the development of web 2.0 technology, internet data has become an important data source for the study of tourism destination image. Taking Nanjing as an example, this paper collected 10077 online reviews about Nanjing from a specialized travel blog site Ma Feng Wo by using the web crawler tool. Through data mining techniques such as word frequency, network semantic analysis, the paper discussed the dimensions of destination perceived image by analyzing TGC (Tourist Generated Comments). First, the results of data analysis show that the importance of dimensions of destination perceived image is different. It is suggested that for the six dimensions of destination perceived image, the tourism attraction is the first level, general infrastructure is the second level, tourist leisure and recreation, tourism environment and atmosphere of the place are the third level, tourist infrastructure is the fourth level. Second, the salient cognitive components in Nanjing's perceived image stem from the dimensions of tourist attractions and public infrastructure. The emotional image of Nanjing is positive. The conative image of Nanjing has been formed and generated the effect of “word of mouth”. In addition, we found that the overall image of Nanjing mainly originated from the perception dimensions of tourism attractions and public infrastructure, which also verified the hierarchy of perception dimensions of destination image. This paper verifies the relevant theories of tourism destination image, enriches the research methods of big data in the field of tourism research, and provides a scientific basis for the construction and development of tourism image in Nanjing.

Key words: big data, destination image, text mining, Nanjing