Semantic social media analysis of Chinese tourists in Switzerland

Zhan Liu (), Jialu Shan (), Nicole Glassey Balet () and Gang Fang ()
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Zhan Liu: University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)
Jialu Shan: International Institute for Management Development (IMD)
Nicole Glassey Balet: University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)
Gang Fang: Hangzhou Dianzi University

Information Technology & Tourism, 2017, vol. 17, issue 2, No 4, 183-202

Abstract: Abstract In recent years, Sina Weibo, a Twitter-like social network service in China, has attracted attention from scholars in the domain of information systems, as the spread and influence of users’ opinions are increasingly important, particularly in the tourism industry. This study examined the behaviors of Chinese tourists in Switzerland by adopting a semantic-based linked data methodology. A total of 103,778 Weibo messages shared with Swiss locations were collected between January 2013 and April 2015. We addressed questions about Chinese travelers’ profiles, trends in keywords, and differences between first time and repeat visitors. Moreover, we implemented a semantic search engine by employing linked data technologies to provide useful information about Chinese tourists in Switzerland, both for the tourism industry and individual tourists.

Keywords: Semantic web; Linked data; Social media; Tourism; Big data; Chinese tourists (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s40558-016-0066-z

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