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Balancing Privacy and Planning: Using Counterfactuals to Predict and Optimize Tourism in Wakayama City
7 references·0 citing·37 second hopsampled
Balancing Privacy and Planning: Using Counterfactuals to Predict and Optimize Tourism in Wakayama City (2024)Balancing Privacy and Planning: Using Cou…PredicTour: Predicting Mobility Patterns of Tourists Based on Social Media User’s Profiles (2022)PredicTour: Predicting Mobili…A graph-based approach to detecting tourist movement patterns using social media data (2018)A graph-based approach to det…Using GPS Technology to Quantify Human Mobility, Dynamic Contacts and Infectious Disease Dynamics in a Resource-Poor Urban Environment (2013)Using GPS Technology to Quant…Understanding temporal rhythms and travel behaviour at destinations: potential ways to achieve more sustainable travel (2013)Understanding temporal rhythm…Analysing hiker movement patterns using GPS data: Implications for park management (2013)Analysing hiker movement patt…Urban land uses and traffic ‘source-sink areas’: Evidence from GPS-enabled taxi data in Shanghai (2012)Urban land uses and traffic ‘…A Social Network Analysis of Overseas Tourist Movement Patterns in Beijing: the Impact of the Olympic Games (2011)A Social Network Analysis of …The framework of tourism (1979)Qualitative Research Methods for the Social Sciences (2000)Qualitative research: Methods in the social sciences (2006)Social network analysis in sport research: an emerging paradigm (2017)Exploring spatio-temporal changes of city inbound tourism flow: The case of Shanghai, China (2019)Tourists’ digital footprint: The spatial patterns of tourist flows in Qingdao, China (2020)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)Tracking tourists in the digital age (2007)Encyclopedia of Statistics in Quality and Reliability (2008)Evaluating the structure and use of hiking trails in recreational areas using a mixed GPS tracking and graph theory approach (2014)Smartphone GPS tracking—Inexpensive and efficient data collection on recreational movement (2016)Modeling intra-destination travel behavior of tourists through spatio-temporal analysis (2018)Cities and Housing. (1970)Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)A new insight into land use classification based on aggregated mobile phone data (2014)Revealing travel patterns and city structure with taxi trip data (2015)Social Sensing: A New Approach to Understanding Our Socioeconomic Environments (2015)The scaling laws of human travel (2006)Exploring Universal Patterns in Human Home-Work Commuting from Mobile Phone Data (2014)Using Google Location History data to quantify fine-scale human mobility (2018)Measuring spatio-temporal accessibility to emergency medical services through big GPS data (2019)The mobile connection: the cell phone's impact on society (2004)Rhythmanalysis: Space, Time and Everyday Life (2005)The New Mobilities Paradigm (2006)Measuring Emotions in Real Time (2014)Tourist use of public transport at destinations – a review (2014)A comprehensive review of mobile technology use in hospitality and tourism (2018)Citizens as sensors: the world of volunteered geography (2007)Social Media Use in the United States: Implications for Health Communication (2009)Learning patterns of tourist movement and photography from geotagged photos at archaeological heritage sites in Cuzco, Peru (2020)Monitoring the Spatial Spread of COVID-19 and Effectiveness of Control Measures Through Human Movement Data: Proposal for a Predictive Model Using Big Data Analytics (2020)Using geotagged tweets to track population movements to and from Puerto Rico after Hurricane Maria (2020)Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose (2021)Location-Based Service Insights: A Comprehensive Review of Data Mining Objects (2024)Culture Fingerprint: Identification of Culturally Similar Urban Areas Using Google Places Data (2025)Spatio-Temporal Tourist Behavior (STTB) under digital footprints: a systematic literature review (2025)
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References

  • 2012Urban land uses and traffic ‘source-sink areas’: Evidence from GPS-enabled taxi data in Shanghai429 cited
  • 2013Using GPS Technology to Quantify Human Mobility, Dynamic Contacts and Infectious Disease Dynamics in a Resource-Poor Urban Environment252 cited
  • 2011A Social Network Analysis of Overseas Tourist Movement Patterns in Beijing: the Impact of the Olympic Games161 cited
  • 2018A graph-based approach to detecting tourist movement patterns using social media data87 cited
  • 2013Analysing hiker movement patterns using GPS data: Implications for park management82 cited
  • 2013Understanding temporal rhythms and travel behaviour at destinations: potential ways to achieve more sustainable travel57 cited
  • 2022PredicTour: Predicting Mobility Patterns of Tourists Based on Social Media User’s Profiles35 cited

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