地理科学 ›› 2015, Vol. 35 ›› Issue (7): 814-821.doi: 10.13249/j.cnki.sgs.2015.07.814

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基于社会感知计算的游客时空行为研究

李君轶(), 唐佳, 冯娜   

  1. 陕西师范大学旅游与环境学院,陕西 西安710062
  • 收稿日期:2014-01-20 修回日期:2014-06-05 出版日期:2015-07-20 发布日期:2015-07-20
  • 作者简介:

    作者简介:李君轶(1975-),男,宁夏固原人,博士,教授,硕士生导师,主要从事旅游地理学研究。E-mail:lijunyi9@snnu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41001077/41401639)、陕西师范大学中央高校基本科研业务费专项资金项目(14SZZD03)、2013年国家旅游局旅游业青年专家培养计划(TYETP201344)联合资助

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

摘要:

在情景感知、大数据、移动互联网和物联网发展的大背景下,迎合社会感知计算发展的趋势,探讨旅游社会感知计算内涵及其应用。在分析了现实地理世界、游客行为研究和社会感知计算之间关系的基础上,探讨旅游管理、传感器、游客活动和推理机的相互作用,构建了四位一体的游客行为社会感知计算概念模型。同时以西安国内游客为例,在新浪微博数据的支持和旅游社会感知计算框架下,探讨西安国内游客的时空共现和旅游流空间转移,探明了游客之间的相互关系和旅游空间行为及旅游流空间网络特征,为游客行为研究提供了思路和借鉴。同时在目前社会感知计算研究进展的基础上,展望了旅游社会感知计算未来的发展方向。

关键词: 游客行为, 社会感知计算, 大数据, 旅游数字足迹, 计算地理学

Abstract:

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

中图分类号: 

  • F590