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Activity knowledge discovery: Detecting collective and individual activities with digital footprints and open source geographic data
16 references·7 citing·41 second hop
Activity knowledge discovery: Detecting collective and individual activities with digital footprints and open source geographic data (2020)Activity knowledge discovery: Detecting c…Exploring Millions of Footprints in Location Sharing Services (2021)Exploring Millions of Footpri…Human mobility and socioeconomic status: Analysis of Singapore and Boston (2018)Human mobility and socioecono…Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns (2017)Coupling mobile phone and soc…Urban human mobility data mining: An overview (2016)Urban human mobility data min…Activity patterns, socioeconomic status and urban spatial structure: what can social media data tell us? (2016)Activity patterns, socioecono…Mining point-of-interest data from social networks for urban land use classification and disaggregation (2015)Mining point-of-interest data…Extracting and understanding urban areas of interest using geotagged photos (2015)Extracting and understanding …Exploration of spatiotemporal and semantic clusters of Twitter data using unsupervised neural networks (2015)Exploration of spatiotemporal…Urban activity pattern classification using topic models from online geo-location data (2014)Urban activity pattern classi…Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data (2014)Intra-Urban Human Mobility an…Exploring human mobility with multi-source data at extremely large metropolitan scales (2014)Exploring human mobility with…Assessment of the accuracy of GeoNames gazetteer data (2013)Assessment of the accuracy of…Mining Travel Patterns from Geotagged Photos (2012)Mining Travel Patterns from G…Exploratory data analysis of activity diary data: a space–time GIS approach (2011)Exploratory data analysis of …Limits of Predictability in Human Mobility (2010)Limits of Predictability in H…Understanding individual human mobility patterns (2008)Understanding individual huma…Understanding factors associated with individuals’ non-mandatory activities using machine learning and SHAP interpretation: A case study of Guangzhou, China (2024)Understanding factors associa…Research on Resident Behavioral Activities Based on Social Media Data: A Case Study of Four Typical Communities in Beijing (2024)Research on Resident Behavior…Reconstructing human activities via coupling mobile phone data with location-based social networks (2023)Reconstructing human activiti…Perception of urban population characteristics through dietary taste patterns based on takeout data (2022)Perception of urban populatio…Investigating Human Travel Patterns from an Activity Semantic Flow Perspective: A Case Study within the Fifth Ring Road in Beijing Using Taxi Trajectory Data (2022)Investigating Human Travel Pa…Graph-based representation for identifying individual travel activities with spatiotemporal trajectories and POI data (2022)Graph-based representation fo…Exploitation of Aggregate Mobility Sensing Data for the Synthesis of Disaggregate Multimodal Tours in Megacities (2021)Exploitation of Aggregate Mob…Citizens as sensors: the world of volunteered geography (2007)The wisdom hierarchy: representations of the DIKW hierarchy (2007)OpenStreetMap: User-Generated Street Maps (2008)Beyond Word2vec: An approach for urban functional region extraction and identification by combining Place2vec and POIs (2018)Social Media data: Challenges, opportunities and limitations in urban studies (2018)Discovering the tourists' behaviors and perceptions in a tourism destination by analyzing photos' visual content with a computer deep learning model: The case of Beijing (2019)The origin of bursts and heavy tails in human dynamics (2005)The scaling laws of human travel (2006)A universal model for mobility and migration patterns (2012)Friendship and mobility (2011)Discovering themes and trends in transportation research using topic modeling (2017)Social-media data for urban sustainability (2018)Applications of artificial intelligence for disaster management (2020)Predicting Depression via Social Media (2021)Reality mining: sensing complex social systems (2005)Modelling the scaling properties of human mobility (2010)Determining Sample Size for Research Activities (1970)Mapping the world's photos (2009)Travel route recommendation using geotags in photo sharing sites (2010)Exploring the travel behaviors of inbound tourists to Hong Kong using geotagged photos (2014)User-Generated Content as a Research Mode in Tourism and Hospitality Applications: Topics, Methods, and Software (2014)Mapping Cilento: Using geotagged social media data to characterize tourist flows in southern Italy (2016)Agent-based modeling: Methods and techniques for simulating human systems (2002)A scalable framework for spatiotemporal analysis of location-based social media data (2015)Incorporating spatial interaction patterns in classifying and understanding urban land use (2015)Uncovering the spatial structure of mobility networks (2015)A comparison of string distance metrics for name-matching tasks (2003)Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice (2011)Delineating urban functional areas with building-level social media data: A dynamic time warping (DTW) distance based k-medoids method (2016)Extracting urban functional regions from points of interest and human activities on location‐based social networks (2017)Spatial variations in urban public ridership derived from GPS trajectories and smart card data (2018)Portraying the spatial dynamics of urban vibrancy using multisource urban big data (2019)Multiscale dynamic human mobility flow dataset in the U.S. during the COVID-19 epidemic (2020)The Geography of Transport Systems (2020)Computational Social Science (2009)The statistical physics of cities (2019)Human mobility data in the COVID-19 pandemic: characteristics, applications, and challenges (2021)Mobile phone location data for disasters: A review from natural hazards and epidemics (2022)Geo-located Twitter as proxy for global mobility patterns (2014)Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs (2014)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)
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References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2010Limits of Predictability in Human Mobility3,230 cited
  • 2021Exploring Millions of Footprints in Location Sharing Services685 cited
  • 2015Mining point-of-interest data from social networks for urban land use classification and disaggregation337 cited
  • 2015Extracting and understanding urban areas of interest using geotagged photos310 cited
  • 2017Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns298 cited
  • 2014Urban activity pattern classification using topic models from online geo-location data289 cited
  • 2018Human mobility and socioeconomic status: Analysis of Singapore and Boston237 cited
  • 2012Mining Travel Patterns from Geotagged Photos229 cited
  • 2014Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data216 cited
  • 2011Exploratory data analysis of activity diary data: a space–time GIS approach190 cited
  • 2016Activity patterns, socioeconomic status and urban spatial structure: what can social media data tell us?181 cited
  • 2014Exploring human mobility with multi-source data at extremely large metropolitan scales153 cited
  • 2015Exploration of spatiotemporal and semantic clusters of Twitter data using unsupervised neural networks

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137 cited
  • 2016Urban human mobility data mining: An overview132 cited
  • 2013Assessment of the accuracy of GeoNames gazetteer data127 cited
  • Cited by

    • 2023Reconstructing human activities via coupling mobile phone data with location-based social networks24 cited
    • 2022Graph-based representation for identifying individual travel activities with spatiotemporal trajectories and POI data21 cited
    • 2022Investigating Human Travel Patterns from an Activity Semantic Flow Perspective: A Case Study within the Fifth Ring Road in Beijing Using Taxi Trajectory Data15 cited
    • 2024Understanding factors associated with individuals’ non-mandatory activities using machine learning and SHAP interpretation: A case study of Guangzhou, China14 cited
    • 2022Perception of urban population characteristics through dietary taste patterns based on takeout data9 cited
    • 2024Research on Resident Behavioral Activities Based on Social Media Data: A Case Study of Four Typical Communities in Beijing4 cited
    • 2021Exploitation of Aggregate Mobility Sensing Data for the Synthesis of Disaggregate Multimodal Tours in Megacities2 cited