SCIENTIA GEOGRAPHICA SINICA ›› 2015, Vol. 35 ›› Issue (7): 814-821.doi: 10.13249/j.cnki.sgs.2015.07.814

• Orginal Article • Previous Articles     Next Articles

Tourists’ Spatio-temporal Behavior Based on Socially Aware Computing

Jun-yi LI(), Jia TANG, Na FENG   

  1. School of Tourism and Environment,Shaanxi Normal University, Xi’an, Shaanxi 710062, China
  • Received:2014-01-20 Revised:2014-06-05 Online:2015-07-20 Published:2015-07-20


From the traditional geography to the computational geography, then to the socially aware computing now, the research of tourism geography changes revolutionarily. In the information society where the concept of big data arises at a historic moment, tourists’ behavior research has changed in such aspects as the data acquisition and calculation, the result feedback and so on. In the Big Data era, it is a tendency that human life is becoming more and more digital and networked by using sensor technology and situation aware technology to perceive human social behavior. Under this background, through a stepwise analysis of the development and connotation of socially aware computing, the tourism socially aware computing and its characteristics are confirmed. Based on predecessors' research, this paper analyzed the relationship between socially aware computing, tourists’ behavior research and the geographic world, and put forward the concept model of socially aware computing of tourists’ behavior by thoroughly analyzing the relationship among tourism management, sensing equipment, tourist activity and inference engine. Besides, this article also put forward socially aware computation analysis model and the study process of tourists’ spatio-temporal behavior. And taking the domestic tourists in Xi’an as a case, we discussed tourists’ spatio-temporal co-occurrence and tourists’ flow spatial structure in Xi’an, and studied the mutual relationship between tourists and their spatial behavior and the characteristics of network based on socially aware computation model. The result shows that the relationship between tourists is relatively weak, which is different from the resident, because sample data in this article are limited and the relationship of tourists is loose. In addition, by measuring district correlation, district transfer correlation and transfer tendency, the research also presents that there are very stable directed tourist flow transfer phenomena existing in the Bell Tower District, Qujiang District and Lintong District, so they can form an "iron triangle" of tourism development in Xi’an. The data were obtained from the travel notes and photos which tourists published in Sina Weibo. We are looking forward to providing a train of thought and reference for related research. Under the background of Big Data, the research of tourism is in the preliminary stage, so its correlation studies are limited. From other research fields, we can find that the researches of socially aware computing are concentrated on socially aware modeling, social data awareness, social interaction and rule analysis, intelligent and ancillary support and application. We anticipated the research direction of tourists socially aware computing in the future based on the current research progress of socially aware computing. In the future, this field will focus on the socially aware modeling of tourists’ behavior, the real time awareness and the tourists’ behavior data mining, tourists’ behavior rule analysis, the study under the intelligent and ancillary support, the application of “Smarter Tourism” and the moving socially aware computation.

Key words: tourists’ behavior, socially aware computing, big data, tourism digital footprint, computational geography

CLC Number: 

  • F590