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Profiling unmanned aerial vehicle photography tourists

Author

Listed:
  • Xiliang Chen
  • Gang Li
  • Lan Yang
  • Qifan Nie
  • Xinyue Ye
  • Yanjun Liang
  • Tingting Xu

Abstract

Based on User Generated Content (UGC) data, namely Unmanned Aerial Vehicle (UAV) photos and corresponding social media captions, this paper uses the methods of AI cognitive analysis and GIS spatial analysis to profile UAV photography tourists. The findings of this study reveal that UAV photography tourists primarily take pictures of natural landscapes, most of which do not contain humans, concentrated in the coastal regions. Additionally, a sentiment analysis indicates that tourists’ opinions of photography are typically positive.

Suggested Citation

  • Xiliang Chen & Gang Li & Lan Yang & Qifan Nie & Xinyue Ye & Yanjun Liang & Tingting Xu, 2020. "Profiling unmanned aerial vehicle photography tourists," Current Issues in Tourism, Taylor & Francis Journals, vol. 23(14), pages 1705-1710, July.
    • Handle: RePEc:taf:rcitxx:v:23:y:2020:i:14:p:1705-1710
    DOI: 10.1080/13683500.2019.1653832
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    Cited by:

    1. Yang Song & Huan Ning & Xinyue Ye & Divya Chandana & Shaohua Wang, 2022. "Analyze the usage of urban greenways through social media images and computer vision," Environment and Planning B, , vol. 49(6), pages 1682-1696, July.
    2. Xiliang Chen & Gang Li & Muhammad Sajid Mehmood & Qifan Nie & Jie Yu, 2023. "Integration and differentiation: comparison of photography behaviors using unmanned aerial vehicle data in China and Europe," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.

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