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Discovering Common Pathways Across Users’ Habits in Mobility Data
11 references·0 citing·43 second hop
Discovering Common Pathways Across Users’ Habits in Mobility Data (2019)Discovering Common Pathways Across Users’…Identifying Points of Interest and Similar Individuals from Raw GPS Data (2020)Identifying Points of Interes…Mining Individual Similarity by Assessing Interactions with Personally Significant Places from GPS Trajectories (2018)Mining Individual Similarity …Extracting User Habits from Google Maps History Logs (2018)Extracting User Habits from G…Analyzing large-scale human mobility data: a survey of machine learning methods and applications (2018)Analyzing large-scale human m…Clustering Weekly Patterns of Human Mobility Through Mobile Phone Data (2017)Clustering Weekly Patterns of…Daily and weekly patterns in human mobility. (2012)Daily and weekly patterns in …The computational turn: thinking about the digital humanities (2011)The computational turn: think…Mining Individual Life Pattern Based on Location History (2009)Mining Individual Life Patter…Computational Social Science (2009)Computational Social ScienceUnderstanding mobility based on GPS data (2008)Understanding mobility based …Habit (1903)HabitInferring High-Level Behavior from Low-Level Sensors (2003)Predestination: Inferring Destinations from Partial Trajectories (2006)Learning and inferring transportation routines (2007)What's Your Next Move: User Activity Prediction in Location-based Social Networks (2013)Analysis of human mobility patterns from GPS trajectories and contextual information (2015)Spatio-Temporal Analysis of Passenger Travel Patterns in Massive Smart Card Data (2017)Using GPS to learn significant locations and predict movement across multiple users (2003)Next place prediction using mobility Markov chains (2012)Understanding Human Mobility from Twitter (2015)Human mobility: Models and applications (2018)Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study (2008)A 61-million-person experiment in social influence and political mobilization (2012)Private traits and attributes are predictable from digital records of human behavior (2013)Structural Topic Models for Open‐Ended Survey Responses (2014)Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)You are where you tweet (2010)From mobility data to habits and common pathways (2020)Mining Human Mobility Data to Discover Locations and Habits (2020)Spatiotemporal Analysis of Human Mobility in Greater Tokyo Area Using Hourly 500 m Mobile Spatial Statistics from 2019 to 2021 (2025)Discovering regions of different functions in a city using human mobility and POIs (2012)Comparison of the spatiotemporal mobility patterns among typical subgroups of the actual population with mobile phone data: A case study of Beijing (2020)Heterogeneity in Activity-travel Patterns of Public Transit Users: An Application of Latent Class Analysis (2021)How did human dwelling and working intensity change over different stages of COVID-19 in Beijing? (2021)Modelling the scaling properties of human mobility (2010)Social Sensing: A New Approach to Understanding Our Socioeconomic Environments (2015)Metagraph-Based Life Pattern Clustering With Big Human Mobility Data (2022)Friendship and mobility (2011)Urban Human Mobility (2019)Using data derived from cellular phone locations to estimate visitation to natural areas: An application to water recreation in New England, USA (2020)Trackintel: An open-source Python library for human mobility analysis (2023)Reality mining: sensing complex social systems (2005)The shortest path to happiness (2014)Restricted but satisfied: Google Maps and agency in the mundane life (2023)The Structure of Scientific Revolutions (1963)Methodology of Scientific Research Programmes (1998)Computing Machinery and Intelligence (1950) (2004)CRITICAL QUESTIONS FOR BIG DATA (2012)Big Data, new epistemologies and paradigm shifts (2014)The SAGE Handbook of Social Media Research Methods (2016)Rational Habit Formation: Experimental Evidence from Handwashing in India (2017)IDC theory: habit and the habit loop (2020)Examining the factors influencing adoption of over the top (OTT) services among Indian consumers (2021)
this work references cited by second hop

References

  • 2009Computational Social Science3,359 cited
  • 2008Understanding mobility based on GPS data1,131 cited
  • 2011The computational turn: thinking about the digital humanities344 cited
  • 2009Mining Individual Life Pattern Based on Location History281 cited
  • 2018Analyzing large-scale human mobility data: a survey of machine learning methods and applications167 cited
  • 2017Clustering Weekly Patterns of Human Mobility Through Mobile Phone Data85 cited
  • 1903Habit53 cited
  • 2018Mining Individual Similarity by Assessing Interactions with Personally Significant Places from GPS Trajectories21 cited
  • 2018Extracting User Habits from Google Maps History Logs21 cited
  • 2012Daily and weekly patterns in human mobility.13 cited
  • 2020Identifying Points of Interest and Similar Individuals from Raw GPS Data9 cited

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