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A Smartphone-Based System for Outdoor Data Gathering Using a Wireless Beacon Network and GPS Data: From Cyber Spaces to Senseable Spaces
12 references·2 citing·41 second hop
A Smartphone-Based System for Outdoor Data Gathering Using a Wireless Beacon Network and GPS Data: From Cyber Spaces to Senseable Spaces (2018)A Smartphone-Based System for Outdoor Dat…Analysis of pedestrian behaviors through non-invasive Bluetooth monitoring (2017)Analysis of pedestrian behavi…Urban magnetism through the lens of geo-tagged photography (2015)Urban magnetism through the l…Choosing the Right Home Location Definition Method for the Given Dataset (2015)Choosing the Right Home Locat…Towards a Comparative Science of Cities: Using Mobile Traffic Records in New York, London, and Hong Kong (2014)Towards a Comparative Science…Digital Footprints: Opportunities and Challenges for Online Social Research (2014)Digital Footprints: Opportuni…Data Preprocessing in Data Mining (2014)Data Preprocessing in Data Mi…The use of Bluetooth for analysing spatiotemporal dynamics of human movement at mass events: A case study of the Ghent Festivities (2011)The use of Bluetooth for anal…Brief encounters: Sensing, modeling and visualizing urban mobility and copresence networks (2010)Brief encounters: Sensing, mo…Brief encounters (2010)Brief encountersMining Mobility Behavior from Trajectory Data (2009)Mining Mobility Behavior from…Digital Footprinting: Uncovering Tourists with User-Generated Content (2008)Digital Footprinting: Uncover…Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Mobile Landscapes: Using Loca…An Efficient Surface Map Creation and Tracking Using Smartphone Sensors and Crowdsourcing (2021)An Efficient Surface Map Crea…Identifying the use of a park based on clusters of visitors' movements from mobile phone data (2019)Identifying the use of a park…Reality mining: sensing complex social systems (2005)Understanding individual human mobility patterns (2008)Urban cycles and mobility patterns: Exploring and predicting trends in a bicycle-based public transport system (2010)User-Generated Content as a Research Mode in Tourism and Hospitality Applications: Topics, Methods, and Software (2014)Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Limits of Predictability in Human Mobility (2010)Comparing and modelling land use organization in cities (2015)A Tale of Ten Cities: Characterizing Signatures of Mobile Traffic in Urban Areas (2016)The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective (2016)The scaling laws of human travel (2006)A universal model for mobility and migration patterns (2012)A Review of Human Mobility Research Based on Big Data and Its Implication for Smart City Development (2020)Next-generation visitation models using social media to estimate recreation on public lands (2020)Social Media and Influencer Marketing for Promoting Sustainable Tourism Destinations: The Instagram Case (2023)The Strength of Weak Ties (1973)Power laws, Pareto distributions and Zipf's law (2005)New Tools for Studying Visitor Behaviours in Museums: A Case Study at the Louvre (2012)Sensing WiFi packets in the air (2014)Me++ (2003)Me++: The Cyborg Self and the Networked City (2003)Dynamic population mapping using mobile phone data (2014)A survey of results on mobile phone datasets analysis (2015)Human mobility: Models and applications (2018)The Presentation of Self in Everyday Life. (1956)The Structure of Scientific Revolutions (1963)Contested Boundaries: Explaining Where Ethnoracial Diversity Provokes Neighborhood Conflict (2016)Sources of Segregation in Social Networks: A Novel Approach Using Facebook (2017)"Humanized Robots": A Proposition of Categories to Understand Virtual Influencers (2021)You are where you tweet (2010)Friendship and mobility (2011)Characterizing International Travel Behavior from Geotagged Photos: A Case Study of Flickr (2016)How friends share urban space: An exploratory spatiotemporal analysis using mobile phone data (2017)A crowdsourced valuation of recreational ecosystem services using social media data: An application to a tropical wetland in India (2018)Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: A case study of Ghent, Belgium (2014)Big data in tourism research: A literature review (2018)The potential impacts of digital technologies on co-production and co-creation (2019)Cityware (2008)Crowds, bluetooth, and rock'n'roll (2013)STAC: A web platform for the comparison of algorithms using statistical tests (2015)Sustainable Development Goal for Quality Education (SDG 4): A study on SDG 4 to extract the pattern of association among the indicators of SDG 4 employing a genetic algorithm (2022)Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges (2023)
this work references cited by second hop

References

  • 2014Data Preprocessing in Data Mining1,374 cited
  • 2006Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis865 cited
  • 2008Digital Footprinting: Uncovering Tourists with User-Generated Content470 cited
  • 2014Digital Footprints: Opportunities and Challenges for Online Social Research381 cited
  • 2011The use of Bluetooth for analysing spatiotemporal dynamics of human movement at mass events: A case study of the Ghent Festivities221 cited
  • 2015Urban magnetism through the lens of geo-tagged photography108 cited
  • 2014Towards a Comparative Science of Cities: Using Mobile Traffic Records in New York, London, and Hong Kong100 cited
  • 2015Choosing the Right Home Location Definition Method for the Given Dataset70 cited
  • 2010Brief encounters: Sensing, modeling and visualizing urban mobility and copresence networks57 cited
  • 2010Brief encounters47 cited
  • 2017Analysis of pedestrian behaviors through non-invasive Bluetooth monitoring38 cited
  • 2009Mining Mobility Behavior from Trajectory Data23 cited

Cited by

  • 2021An Efficient Surface Map Creation and Tracking Using Smartphone Sensors and Crowdsourcing5 cited
  • 2019Identifying the use of a park based on clusters of visitors' movements from mobile phone data5 cited

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