Relationship between Tourist Attractions and the Baidu Index: A Case Study of National 5A Scenic Spots of Xi'an City During National Day Holiday
- 10.2991/icoss-17.2017.1How to use a DOI?
- Baidu index; Tourist attraction; Xi'an tourism; National Day holiday; 5A scenic spot
During Chinese National Day holiday, lots of tourists visit well-known scenic spots leading to heavy overcrowding problems. Consequently, the accurately prediction of tourist numbers for certain small regions/scenic spots within few days is important for tourist attractions management and planning. Most existing methods rely on well-structured statistical data published by the government. However, it usually exists the significant delays, and the statistical data is gathered for long intervals and large regions. These drawbacks lead to an inaccurate prediction of tourist numbers for certain small regions/scenic spots within short periods. In this paper, the popular Baidu Index is employed to predict the tourist flow in national 5A scenic spots of Xi'an city during National Day holidays. A large scale Baidu Index data, from 2012 to 2016 years, is used for overall Xi'an tourism and three national 5A scenic spots, i.e., Terra Cotta Warriors, Huaqing Hot Spring and Dayan Pagoda. The results indicate that the Baidu search index of keyword 'weather' has a weak correlation with tourist volume of Xi'an tourism. While the keywords 'ticket' and 'tourism' has a positive correlation between the increasing Baidu search index and the increasing observed tourist flow.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Kewei Lei AU - Xiaohui Wang AU - Xiaoning Dou PY - 2017/04 DA - 2017/04 TI - Relationship between Tourist Attractions and the Baidu Index: A Case Study of National 5A Scenic Spots of Xi'an City During National Day Holiday BT - Proceedings of the 2017 International Conference on Society Science (ICoSS 2017) PB - Atlantis Press SP - 1 EP - 7 SN - 2352-5398 UR - https://doi.org/10.2991/icoss-17.2017.1 DO - 10.2991/icoss-17.2017.1 ID - Lei2017/04 ER -