Word-of-Mouth Evaluation of Ancient Towns in Southern China Using Web Comments

Yihan Zhang (), Weizhuo Guo, Yanling Sheng and Shanshan Li
Additional contact information
Yihan Zhang: School of Geography and Environmental Economics, Guangdong University of Finance and Economics, Guangzhou 510320, China
Weizhuo Guo: School of Geography and Environmental Economics, Guangdong University of Finance and Economics, Guangzhou 510320, China
Yanling Sheng: School of Geography and Environmental Economics, Guangdong University of Finance and Economics, Guangzhou 510320, China
Shanshan Li: School of Geography and Environmental Economics, Guangdong University of Finance and Economics, Guangzhou 510320, China

Tourism and Hospitality, 2025, vol. 6, issue 1, 1-22

Abstract: With the rapid development of digital networks and communication technologies, traditional word-of-mouth (WOM) has transformed into electronic word-of-mouth (eWOM), which plays a pivotal role in improving the management and service quality of ancient town tourism. This study uses Python web scraping techniques to gather eWOM data from the top ten ancient towns in southern China. Using IPA analysis, the analytic hierarchy process (AHP), Term Frequency–Inverse Document Frequency (TF-IDF), and cluster analysis, we developed a comprehensive eWOM evaluation framework. This framework was employed to perform word frequency analysis, sentiment analysis, topic modeling, and rating analysis, providing deeper insights into tourists’ perceptions. The results reveal several key findings: (1) Transportation infrastructure varies significantly across the towns. Heshun and Huangyao suffer from poor accessibility, while the remaining towns benefit from the developed transportation network of the Yangtze River Delta. (2) The volume of eWOM is strongly influenced by seasonal patterns and was notably impacted by the COVID-19 pandemic. (3) The majority of tourists express positive sentiments toward the ancient towns, with a focus on the available facilities. Their highest levels of satisfaction, however, are associated with the scenic landscapes. (4) A comprehensive eWOM analysis suggests that Wuzhen and Xidi–Hongcun are the most popular tourist destinations, while Zhujiajiao, Huangyao, Zhouzhuang, and Nanxun exhibit lower levels of both attention and visitor satisfaction.

Keywords: electronic word-of-mouth (eWOM); evaluation analysis; web crawler; ancient towns (search for similar items in EconPapers)
JEL-codes: Z3 Z30 Z31 Z32 Z33 Z38 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2673-5768/6/1/25/pdf (application/pdf)
https://www.mdpi.com/2673-5768/6/1/25/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jtourh:v:6:y:2025:i:1:p:25-:d:1588175

Access Statistics for this article

Tourism and Hospitality is currently edited by Mr. Philip Li

More articles in Tourism and Hospitality from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().