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 attractions in Yan’an City is high. (3) The
network structure of tourism flow in the case has the
spatial characteristics of low density, ‘one level
and multicore’ and significant small
network groups. (4) There are correlations and
differences between network attention and tourism flow
in the sites in question. Based on the differences
between them, the attractions are classified into four types: high-high,
high-low, low-high and low-low. In response to the above
findings, this study proposes the principle of
‘precision identification and classification’, and proposes
targeted development strategies such as creating high-quality
regional tourist routes, promoting the digital development of
tourist attractions, and innovating the ways to promote attractions.