The network characteristics of classic red tourist attractions in Shaanxi province, China

Tourism flow is a significant tourism phenomenon and a hot topic of tourism geography research. This study, based on the perspective of combining ‘virtual’ and ‘reality’, takes 13 classic red tourism scenic areas in Shaanxi province as examples. It constructs a multi-source data network attention evaluation index and adopts social network analysis method to explore the network attention and tourism flow of the study case, and further investigates the relationship between the two. The study shows that: (1) The case sites have formed a spatial layout of the ‘dense in the north and sparse in the south’. Among them, the total number of attractions in northern Shaanxi is the largest and most are concentrated in Yan’an; the total number of attractions in southern Shaanxi is the smallest and most scattered. (2) The overall network attention of the case sites is low, and there is variability in network attention of different types of tourist attractions, among which network attention of the att..., Based on the previous analysis, there are primarily two research methods for studying network attention. The first method is based on Baidu index, while the second method involves constructing network attention using multiple sources of data.However, when the research area encompasses multiple tourism resources, it is difficult to obtain comprehensive and reliable data solely through Baidu index. Moreover, due to the multitude of tourism resources in this study, the reliability and accuracy of using a single data source are relatively low.Therefore, it is necessary to construct a network attention index for case studies. Based on the reference to previous research and considering the comprehensiveness, accuracy, and availability of data, this study selected five Chinese social platforms, namely Ctrip, WeChat, Baidu, 360, and Mafengwo, as the sources of network attention data (all data were collected until January 1, 2023.).The specific steps are as follows: firstly, data collection is c..., , # **The network characteristics of classic red tourist attractions in Shaanxi province, China**

Based on the previous analysis, there are primarily two research methods for studying network attention. The first method is based on Baidu index, while the second method involves constructing network attention using multiple sources of data. However, when the research area encompasses multiple tourism resources, it is difficult to obtain comprehensive and reliable data solely through the Baidu index. Moreover, due to the multitude of tourism resources in this study, the reliability and accuracy of using a single data source are relatively low. Therefore, it is necessary to construct a network attention index for case studies. Based on the reference to previous research and considering the comprehensiveness, accuracy, and availability of data, this study selected five Chinese social platforms, namely Ctrip, WeChat, Baidu, 360, and Mafengwo, as the sources of network attention data (all dat...