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Semantic social media analysis of Chinese tourists in Switzerland

Author

Listed:
  • 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)

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.

Suggested Citation

  • Zhan Liu & Jialu Shan & Nicole Glassey Balet & Gang Fang, 0. "Semantic social media analysis of Chinese tourists in Switzerland," Information Technology & Tourism, Springer, vol. 0, pages 1-20.
    • Handle: RePEc:spr:infott:v::y::i::d:10.1007_s40558-016-0066-z
    DOI: 10.1007/s40558-016-0066-z
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    References listed on IDEAS

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    1. Bernard J. Jansen & Mimi Zhang & Kate Sobel & Abdur Chowdury, 2009. "Twitter power: Tweets as electronic word of mouth," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(11), pages 2169-2188, November.
    2. Chiara Francalanci & Ajaz Hussain, 2016. "Discovering social influencers with network visualization: evidence from the tourism domain," Information Technology & Tourism, Springer, vol. 16(1), pages 103-125, March.
    3. Guan, Wanqiu & Gao, Haoyu & Yang, Mingmin & Li, Yuan & Ma, Haixin & Qian, Weining & Cao, Zhigang & Yang, Xiaoguang, 2014. "Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 340-351.
    4. Xiang, Zheng & Gretzel, Ulrike, 2010. "Role of social media in online travel information search," Tourism Management, Elsevier, vol. 31(2), pages 179-188.
    5. Li, Yuan & Gao, Haoyu & Yang, Mingmin & Guan, Wanqiu & Ma, Haixin & Qian, Weining & Cao, Zhigang & Yang, Xiaoguang, 2015. "What are Chinese talking about in hot weibos?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 546-557.
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