References

• 2012Discovering regions of different functions in a city using human mobility and POIs1,151 cited
• 2021Exploring Millions of Footprints in Location Sharing Services692 cited
• 2016Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model490 cited
• 2017Extracting urban functional regions from points of interest and human activities on location‐based social networks482 cited
• 2014Discovering Urban Functional Zones Using Latent Activity Trajectories413 cited
• 2017Classifying urban land use by integrating remote sensing and social media data368 cited
• 2015Mining point-of-interest data from social networks for urban land use classification and disaggregation337 cited
• 2018Beyond Word2vec: An approach for urban functional region extraction and identification by combining Place2vec and POIs261 cited
• 2015Inferring trip purposes and uncovering travel patterns from taxi trajectory data261 cited
• 2016The geography of Twitter topics in London220 cited
• 2014Spectral clustering for sensing urban land use using Twitter activity210 cited
• 2018Mapping Urban Functional Zones by Integrating Very High Spatial Resolution Remote Sensing Imagery and Points of Interest: A Case Study of Xiamen, China118 cited
• 2017City dynamics through Twitter: Relationships between land use and spatiotemporal demographics117 cited