Automated Identification of Tourist Activities in Social Media Photographs: a Comparative Analysis Using Visual-based, Textual-based and Joint-based Methods

Authors

  • Shihan (David) Ma Dept. of Tourism, Hospitality and Event Management College of Health and Human Performance University of Florida
  • Andrei P. Kirilenko Dept. of Tourism, Hospitality and Event Management College of Health and Human Performance University of Florida

Keywords:

tourist activity, image identification, Instagram, social media photography, data fusion

Abstract

The studies pertaining to image identification of tourist photographs are mainly dealing with objects/landscapes, while the activities of tourists interacting with these objects is not well researched. The eligible methods to identify in-depth activities are likewise greatly missing. In this paper, we first explore the feasibility of using different data approaches (visual and textual) to identify tourist activities in social media photos. We further develop a multimodal method combining both text-based and visual-based information. The performances of these methods are compared and validated by manual reviewing. The findings confirm that data fusing methodology is improving identification of micro-level activities.

Author Biographies

  • Shihan (David) Ma, Dept. of Tourism, Hospitality and Event Management College of Health and Human Performance University of Florida

    Shihan (David) Ma is a Ph.D. candidate in the Department of Tourism, Hospitality and Event Management at University of Florida. His research concentration is social media data analysis in tourism, regarding tourist perception, behavior, mobility pattern and destination marketing opportunities through big data mining.

  • Andrei P. Kirilenko, Dept. of Tourism, Hospitality and Event Management College of Health and Human Performance University of Florida

    Dr. Andrei P. Kirilenko is Associate Professor in the Department of Tourism, Hospitality and Event Management at the University of Florida. His research interests include big data analysis, data mining, tourism analytics, climate change impacts, and sustainability issues.

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Published

2019-12-20

Issue

Vol. 17 No. 4 (2020)

Section

Articles

License

e-Review of Tourism Research (eRTR) is an international electronic bulletin for tourism research (ISSN:1941-5842). It comprises current tourism research articles, commentaries and reviews by industry professionals. The materials are provided for the personal noncommercial use of registered users of the eRTR, free to individuals and institutions. Copies of articles may be distributed for research or educational purpose, free of charge and without permission. However, commercial use of the eRTR or the articles contained herein is expressly prohibited without the written consent of the publisher.

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  • That the manuscript submitted is his/her own work;
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How to Cite

“Automated Identification of Tourist Activities in Social Media Photographs: a Comparative Analysis Using Visual-based, Textual-based and Joint-based Methods” (2019) e-Review of Tourism Research, 17(4). Available at: https://ertr-ojs-tamu.tdl.org/ertr/article/view/540 (Accessed: 26 July 2024).

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