PurposeIn recent years, electronic word-of-mouth (e-WOM) concerning travel products reflected in online review information has become an important reference for tourists to make their product purchase decisions, while for travel service providers (TSPs), monitoring and improving the e-WOM of their travel products is always an important task. Therefore, based on the online review information, how to capture e-WOM of travel products and find out specific ways to improve the e-WOM is a noteworthy research problem. The purpose of this paper is to develop a method for capturing and analyzing e-WOM toward travel products based on sentiment analysis and stochastic dominance.Design/methodology/approachSpecifically, online review information of travel products is first crawled and preprocessed. Second, sentiment strengths of online review information toward travel products concerning each feature are judged. Then, the matrix of structured online review information toward travel products is formed. Further, the matrix of e-WOM comparisons between any two travel products is constructed, and e-WOM ranking concerning each travel product is determined. Finally, trade-off chart models are constructed to conduct the e-WOM improvement analyses concerning the travel products.FindingsAn empirical study based on the online review information toward six travel products crawled from the Tuniu.com website is given to illustrate the use of the proposed method.Originality/valueThe proposed method can not only realize the real-time e-WOM monitoring to travel products but also be useful for TSPs to improve the e-WOM of their travel products.

Capturing and analyzing e-WOM for travel products: a method based on sentiment analysis and stochastic dominance

The research status of international tourism big data: Visual analysis based on citespace and VOSviewer

The research of tourism big data has attracted extensive attention from the Industry and academics. At present, the research status of tourism big data based on knowledge graph analysis are still relatively rare. [Methods/Process] In this study, SCIE and SSCI from the Core set of Web of Science were selected as data sources to screen out 1130 effective literatures related to tourism big data. CiteSpace and VOSviewer are used to analyze the literature visually. the research results show that:(1) The field of international tourism big data research covers a wide range of areas, with diversified research topics and multidisciplinary crossover dynamics.The hotspots of research are closely related to information technology. (2) The lack of close collaboration among authors can, to a certain extent, hinder the production of high-quality research results. In the future, we need to conduct more detailed research on the application scenarios and limitations of various theories.At the same time, we should strengthen the cooperation between institutions and authors. In addition, need to focus on innovation in data processing and analysis methods

Terraces are the major vehicle for agricultural activities in mountainous areas and are an important component of the agro-cultural heritage landscape. This work explores tourists’ perceived attitudes toward, and characteristics of terraced agro-cultural heritage landscapes based on online web travel notes. A framework of visitor perception types of terraced agricultural cultural heritage landscapes was constructed, and each type was analyzed in a targeted manner. The results obtained can provide a reference for the conservation of heritage farming culture and the development of strategies to improve landscape quality for such sites. This study used crawler software to collect online travelogue data from 3991 notes by visitors to seven note-worthy terraced agro-cultural heritage sites in China and used the ROST Content Mining 6 tool to analyze high-frequency feature words, semantic networks, and sentiment distribution and ten-dency. We found that the tourist perception of the diversity of terraced agro-cultural heritage landscape is rich, with a high overall evaluation. The tourists‘ perceptions focused on four elements: landscape, ecology, culture, and service. They were more likely to have a high perception of the landscape than service, which in turn was higher than culture and ecology. The emotional tendency of tourists‘ perceptions is mainly highly positive and neutral, and negative emotions account for a lower proportion and are mostly mild. 

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Tourists’ Perceived Attitudes toward the Famous Terraced Agricultural Cultural Heritage Landscape in China

Insights into the association rules of destinations can help to understand the possibility of tourists visiting a destination after having traveled from another. These insights are crucial for tourism industries to exploit strategies and travel products and offer improved services. Recently, tourism-related, user-generated content (UGC) big data have provided a great opportunity to investigate the travel behavior of tourists on an unparalleled scale. However, existing analyses of the association of destinations or attractions mainly depend on geo-tagged UGC, and only a few have utilized unstructured textual UGC (e.g., online travel reviews) to understand tourist movement patterns. In this study, we derive the association of destinations from online textual travel reviews. A workflow, which includes collecting data from travel service websites, extracting destination sequences from travel reviews, and identifying the frequent association of destinations, is developed to achieve the goal. A case study of Yunnan Province, China is implemented to verify the proposed workflow. The results show that the popular destinations and association of destinations could be identified in Yunnan, demonstrating that unstructured textual online travel reviews can be used to investigate the frequent movement patterns of tourists. Tourism managers can use the findings to optimize travel products and promote destination management.

Ying Zhang

Papers

A Methodological Workflow for Deriving the Association of Tourist Destinations Based on Online Travel Reviews: A Case Study of Yunnan Province, China