E3S Web Conf.
Volume 292, 20212021 2nd International Conference on New Energy Technology and Industrial Development (NETID 2021)
|Number of page(s)||4|
|Section||Environmental Sustainable Development and Industrial Transformation|
|Published online||09 September 2021|
- He Xiaoxing, Zhang Yanrong, Liu Yu. A study on the Spatio-temporal characteristics of tourist Cave Network attention-- A case study of the five most beautiful tourist caves in China [J]. Karst in China, 2017. 36 (02): 275–282. [Google Scholar]
- Du Mengyi, Yang Xiaoxia, Chen Peng. Research on Spatio-temporal characteristics of Network attention in online Celebrity Scenic spots based on Baidu Index-- A case study of Hongya Cave in Chongqing [J]. Journal of Southwest normal University (Natural Science Edition), 2020545 (06): 72–79. [Google Scholar]
- Xu Fan, you Wei, Anniversary Xing, Hu Meijuan. Research on Spatio-temporal Distribution of attention in Cyberspace based on Baidu Index-- A case study of 5A Scenic spot in Yangtze River Delta [J]. Resource Development and Market, 2016 pr 32 (04): 489–493. [Google Scholar]
- Huang Wensheng. Research on Guangxi Tourism Network attention rate Matrix and Marketing Strategy based on Baidu Index [J]. Regional Research and Development, 201951 38 (05): 101104. [Google Scholar]
- Long Maoxing, Sun Gennian, Ma Lijun, Wang Jiejie. Comparative Analysis of Spatio-temporal Dynamics of Regional Tourism Network attention and passenger flow-- A case study of Sichuan [J]. Regional Research and Development, 2011 Magi 30 (03): 93–97. [Google Scholar]
- Sun Ye, Zhang Honglei, Liu Peixue, Zhang Jie. A study on the Prediction of Daily tourist Volume in Scenic spots based on the attention of tourists' Network-- taking different client Baidu Index as an example [J]. Human Geography, 2017. 32 (03): 152–160. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.