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Analysing trends in the spatio-temporal behaviour patterns of mainland Chinese tourists and residents in Hong Kong based on Weibo data
16 references·15 citing·52 second hop
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References

  • 2003Chaos, crises and disasters: a strategic approach to crisis management in the tourism industry1,146 cited
  • 2010Urban tourism research: Recent progress and current paradoxes983 cited
  • 2014Geo-located Twitter as proxy for global mobility patterns675 cited
  • 1995Progress in tourism, recreation and hospitality management564 cited
  • 2014Mapping Crime: Understanding Hot Spots553 cited
  • 2000The Tourist-Historic City546 cited
  • 2015Identification of tourist hot spots based on social networks: A comparative analysis of European metropolises using photo-sharing services and GIS363 cited
  • 2007Tracking tourists in the digital age357 cited
  • 2008The Effects of a Targeted Intervention to Reduce Problem Behaviors267 cited
  • 2015Social media and crisis management: CERC, search strategies, and Twitter content257 cited
  • 2016Measuring tourism destinations using mobile tracking data255 cited
  • 2017“I will never go to Hong Kong again!” How the secondary crisis communication of “Occupy Central” on Weibo shifted to a tourism boycott192 cited
  • 2016Understanding the tourist mobility using GPS: Where is the next place?185 cited
  • 2007Tracking technologies and urban analysis157 cited
  • 2016Delineation of an urban agglomeration boundary based on Sina Weibo microblog ‘check-in’ data: A case study of the Yangtze River Delta

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155 cited
  • 2009Tourist Mobility and Advanced Tracking Technologies152 cited
  • Cited by

    • 2020Tourism Flow Between Major Cities During China’s National Day Holiday: A Social Network Analysis Using Weibo Check-in Data42 cited
    • 2021Understanding the perceived satisfaction and revisiting intentions of lodgers in a restricted service scenario: evidence from the hotel industry in quarantine34 cited
    • 2020Where day trippers and tourists go: comparing the spatio-temporal distribution of Mainland Chinese visitors in Hong Kong using Weibo data24 cited
    • 2021Toward travel pattern aware tourism region planning: a big data approach22 cited
    • 2022Assessing Reliability of Chinese Geotagged Social Media Data for Spatiotemporal Representation of Human Mobility21 cited
    • 2024Understanding attractions’ connection patterns based on intra-destination tourist mobility: A network motif approach19 cited
    • 2020RETRACTED: Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo19 cited
    • 2025Promoting accessibility for sustainable tourism: a spatial analysis of tourist attractions and public transportation networks in Bangkok16 cited
    • 2022Comparing the spatiotemporal behavior patterns of local, domestic and overseas tourists in Beijing based on multi-source social media big data16 cited
    • 2023An analysis on the spatiotemporal behavior of inbound tourists in Jiaodong Peninsula based on Flickr geotagged photos15 cited
    • 2022Depicting urban multi-scale tourist activity spaces using digital footprints for smart destinations13 cited
    • 2025Exploring the relationship between the tourist behavior and the spatial characteristics for rural tourism13 cited
    • 2024Investigating Resident–Tourist Sharing of Urban Public Recreation Space and Its Influencing Factors9 cited
    • 2021Spatial-temporal analysis of retail and services using Facebook Places data: a case study in Brno, Czech Republic9 cited
    • 2025Spatial Mismatch Between Transportation Development and Tourism Spatial Vitality in Yunnan Province in the Context of Urban–Rural Integration5 cited