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Reconstructing human activities via coupling mobile phone data with location-based social networks

16 references·7 citing·50 second hopsampled

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References

2014Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs857 cited
2012Measurement, Optimization, and Impact of Health Care Accessibility: A Methodological Review696 cited
2017Extracting urban functional regions from points of interest and human activities on location‐based social networks470 cited
2009Eigenbehaviors: identifying structure in routine439 cited
2017Evaluating cities' vitality and identifying ghost cities in China with emerging geographical data383 cited
2013Understanding urban human activity and mobility patterns using large-scale location-based data from online social media315 cited
2017Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns298 cited
2016The TimeGeo modeling framework for urban mobility without travel surveys295 cited
2015Analysis of human mobility patterns from GPS trajectories and contextual information275 cited
2010Does Urban Mobility Have a Daily Routine? Learning from the Aggregate Data of Mobile Networks266 cited
2008Critical Factors for Active Transportation to School Among Low-Income and Minority Students260 cited
2013A review of urban computing for mobile phone traces254 cited
2015Inferring trip purposes and uncovering travel patterns from taxi trajectory data254 cited
2015

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Discovering urban activity patterns in cell phone data

236 cited

2015Uncovering the spatial structure of mobility networks200 cited

2016Activity patterns, socioeconomic status and urban spatial structure: what can social media data tell us?181 cited

Cited by

2023Multi-day activity pattern recognition based on semantic embeddings of activity chains18 cited
2024From cell tower location to user location: Understanding the spatial uncertainty of mobile phone network data in human mobility research15 cited
2023Generating and understanding human daily activity sequences using Time-Varying Markov Chain models11 cited
2024How urban environments affect public sentiment and physical activity using a cognitive computing framework9 cited
2024Understanding the route choice behavior of metro passenger using the smartphone applications7 cited
2024Identifying urban land use through higher-order spatial interactions6 cited
2025A visitor-enriched census in the U.S. cities using large-scale mobile positioning data5 cited