Journal
TOURISM MANAGEMENT
Volume 74, Issue -, Pages 276-289Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.tourman.2019.03.009
Keywords
Online travel reviews; Semantic association analysis; Opinion mining; Social network analysis
Funding
- National Natural Science Foundation of China [71562009, 71562008, 71602092]
- Key Research Institute of Philosophies and Social Sciences in Guangxi Universities [17ZD002]
- Innovation Project of Guangxi Graduate Education [YCSW2018162]
- Natural Science Foundation of Anhui Province [1608085QG168]
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Online tourism reviews provide a crucial source of information for the tourism industry, and determining whether they can be effectively identified is key to influencing tourism decision-making. The purpose of this paper is to identify themes and compare differences in online travel reviews. A semantic association analysis was applied to extract thematic words and construct a semantic association network from 165,429 reviews obtained from three major online travel agencies (OTAs) in China. The findings show that there are apparent discrepancies on these platforms in terms of thematic words, the distribution of topics, structural properties and community relationships. In particular, the results of network visualization can clearly identify hot topics and the social network relationships of thematic words. The proposed analytical framework expands our understanding of the methodological challenges and offers novel insights for mining the opinions for the benefit of tourists, hotels and tourism enterprises and OTAs.
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