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Visualizing Social and Behavior Change due to the Outbreak of COVID-19 Using Mobile Phone Location Data
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Visualizing Social and Behavior Change due to the Outbreak of COVID-19 Using Mobile Phone Location Data (2021)Visualizing Social and Behavior Change du…Insights into population behavior during the COVID-19 pandemic from cell phone mobility data and manifold learning (2021)Insights into population beha…Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020 (2020)Fear, lockdown, and diversion…Spatiotemporal Analysis of Human Mobility in Greater Tokyo Area Using Hourly 500 m Mobile Spatial Statistics from 2019 to 2021 (2025)Spatiotemporal Analysis of Hu…Visualizing population mobility from spatiotemporally aggregated mobile phone data via a 3D gradient approach (2022)Visualizing population mobili…The relationship between mobile broadband usage and user mobility with lockdown restrictions in Spain (2022)The relationship between mobi…Generation of individual daily trajectories by GPT-2 (2022)Generation of individual dail…Changes in mobility amid the COVID-19 pandemic in Sapporo City, Japan: An investigation through the relationship between spatiotemporal population density and urban facilities (2022)Changes in mobility amid the …Valuing mortality risk reductions for environmental policyCOVID-Induced Economic Uncertainty (2020)Determinants of Disparities in Covid-19 Job Losses (2020)The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data (2020)The impact of COVID-19 on small business outcomes and expectations (2020)The Approximation of One Matrix by Another of Lower Rank (1936)Aggregated mobility data could help fight COVID-19 (2020)The socio-economic implications of the coronavirus pandemic (COVID-19): A review (2020)How did human dwelling and working intensity change over different stages of COVID-19 in Beijing? (2021)Influence of trip distance and population density on intra-city mobility patterns in Tokyo during COVID-19 pandemic (2022)The exciting potential and daunting challenge of using GPS human-mobility data for epidemic modeling (2024)Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)Modelling the scaling properties of human mobility (2010)Modeling and generating human mobility trajectories using transformer with day encoding (2023)Profiling Public Transit Passenger Mobility Using Adversarial Learning (2023)Mobile Phone Use and Mental Health. A Review of the Research That Takes a Psychological Perspective on Exposure (2018)COVID ‐19 and the Demand for Online Food Shopping Services: Empirical Evidence from Taiwan (2020)Online Learning: A Panacea in the Time of COVID-19 Crisis (2020)Discovering regions of different functions in a city using human mobility and POIs (2012)Dynamic population mapping using mobile phone data (2014)HMS-PAU-IN: A heterogeneous multi-scale spatiotemporal interaction network model for population analysis units (2025)Applying mobile phone data to travel behaviour research: A literature review (2017)Evaluating the effect of demographic factors, socioeconomic factors, and risk aversion on mobility during the COVID-19 epidemic in France under lockdown: a population-based study (2020)Insights into the impact of COVID-19 on household travel and activities in Australia – The early days under restrictions (2020)The impact of COVID-19 pandemic on the fundamental urban mobility theories using transit data from Singapore (2023)Influences of COVID-19 pandemic on travel patterns across past, present, and future (2024)Liberation from location ties: A descriptive systematic review of shifts in location perception during and after the COVID-19 pandemic (2025)The scaling laws of human travel (2006)A universal model for mobility and migration patterns (2012)
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References

  • 2020Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020738 cited
  • 2021Insights into population behavior during the COVID-19 pandemic from cell phone mobility data and manifold learning60 cited

Cited by

  • 2022Generation of individual daily trajectories by GPT-215 cited
  • 2022Changes in mobility amid the COVID-19 pandemic in Sapporo City, Japan: An investigation through the relationship between spatiotemporal population density and urban facilities11 cited
  • 2022Visualizing population mobility from spatiotemporally aggregated mobile phone data via a 3D gradient approach9 cited
  • 2025Spatiotemporal Analysis of Human Mobility in Greater Tokyo Area Using Hourly 500 m Mobile Spatial Statistics from 2019 to 20214 cited
  • 2022The relationship between mobile broadband usage and user mobility with lockdown restrictions in Spain3 cited

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