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Integrating GPS trajectory and topics from Twitter stream for human mobility estimation

  • Satoshi Miyazawa
  • Xuan Song
  • Tianqi Xia
  • Ryosuke Shibasaki
  • Hodaka Kaneda
Research Article
  • 24 Downloads

Abstract

Understanding urban dynamics and large-scale human mobility will play a vital role in building smart cities and sustainable urbanization. Existing research in this domain mainly focuses on a single data source (e.g., GPS data, CDR data, etc.). In this study, we collect big and heterogeneous data and aim to investigate and discover the relationship between spatiotemporal topics found in geo-tagged tweets and GPS traces from smartphones. We employ Latent Dirichlet Allocation-based topic modeling on geo-tagged tweets to extract and classify the topics. Then the extracted topics from tweets and temporal population distribution from GPS traces are jointly used to model urban dynamics and human crowd flow. The experimental results and validations demonstrate the efficiency of our approach and suggest that the fusion of cross-domain data for urban dynamics modeling is more practical than previously thought.

Keywords

GPS trajectory human mobility SNS location-based social network (LBSN) topic modeling data mining spatiotemporal topic 

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Notes

Acknowledgements

This work was partially supported by JST, Strategic International Collaborative Research Program (SICORP); Grant in-Aid for Scientific Research B (17H01784) and Grant in-Aid for Young Scientists (26730113) of Japan’s Ministry of Education, Culture, Sports, Science, and Technology (MEXT). We specially thank ZENRIN DataCom CO., LTD for the provision of GPS data and their support, and Nightley Inc. for geo-tagged tweets.

Supplementary material

11704_2017_6464_MOESM1_ESM.pptx (12 mb)
Integrating GPS trajectory and topics from Twitter stream sor human mobility estimation

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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Satoshi Miyazawa
    • 1
  • Xuan Song
    • 2
  • Tianqi Xia
    • 1
  • Ryosuke Shibasaki
    • 2
  • Hodaka Kaneda
    • 3
  1. 1.Department of Socio-Cultural Environmental Studies, Graduate School of Frontier SciencesThe University of TokyoChibaJapan
  2. 2.Center for Spatial Information ScienceThe University of TokyoKashiwaJapan
  3. 3.Zenrin DataCom Co’LtdTokyoJapan

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