Advancing reliability assessment of venue-reference social media data for enhanced domestic tourism development

Huy Quan Vu (), Shah Jahan Miah (), Haiyang Xia (), Gang Li (), Birgit Muskat () and Rob Law ()
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Huy Quan Vu: Deakin University
Shah Jahan Miah: University of Newcastle
Haiyang Xia: Australian National University
Gang Li: Deakin University
Birgit Muskat: Australian National University
Rob Law: University of Macau

Information Technology & Tourism, 2023, vol. 25, issue 3, No 8, 433-451

Abstract: Abstract The aim of this research is to assess the reliability of venue check-in data. We focus on resident mobility and assess how venue check-in data can provide valuable insights into residents’ movement in tourist destinations. Understanding resident’s mobility and related activities is necessary for strategic planning and decision making for destination managers. Venue-referenced social media data (VR-SMD) is a new type of data and can provide insights into resident’s mobility and behavior. While VR-SMD is available on various social media platforms, their reliability to capture resident movement and activities has not been fully realized. We present an analytical approach to assess and demonstrate how VR-SMD, specifically venue check-in data, can be used to capture resident mobility and activities, with illustrative examples from the United States of America, United Kingdom, and Singapore. Results and analysis indicate that tourism managers and government organizations can exploit VR-SMD for domestic tourism development.

Keywords: Mobility tracking; VR-SMD; Venue check-in; Domestic tourism (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s40558-023-00254-z

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