Scenic Image Research Based on Big Data Analysis - Take China's Four Ancient Cities as an Example

• Rui Liang,
• Hanwen Guo,
• Jiayu Liu,
• Ziyang Liu,

Vol. 14, No. 7, July 31, 2020
10.3837/tiis.2020.07.002, Download Paper (Free):

• Scenic Image
• Big data
• Ancient city
• Content Analysis Method
• Social Network Analysis
• Entropy Weight Method

Abstract

This paper aims to compare the scenic images of four ancient Chinese cities including Lijiang, Pingyao, Huizhou and Langzhong, so as to provide specific development strategies for the ancient cities. In this paper, the ancient cities’ scenic images are divided into three sub-indexes and eight evaluation dimensions. Based on this, the study first uses Python software to collect tourists’ online comments on the four ancient cities. Then, the social network analysis method is used to build a high-frequency keywords matrix of tourist comments and the R language is used to generate a visual network graph. After this, the entropy weight method is used to determine the weights and values of eight evaluation dimensions. Finally, the tourists’ overall satisfaction indexes of the four ancient cities are calculated accordingly. The results show that (1) the overall satisfaction of Lijiang is the highest, while that of Huizhou is the lowest; (2) from the weight of each evaluation dimension, it can be seen that tourists care more about the national culture and historical culture; (3) from tourists’ satisfaction index on each evaluation dimension of the four ancient cities, we can find that the four ancient cities has their own advantages and disadvantages in tourism development. (4) local tourism-related institutions should strengthen their advantages and improve their deficiencies so as to enhance tourists’ overall image of the ancient city.

Statistics

Cite this article