Mobility Pattern Identification Based on Mobile Phone Data

  • Chao YangEmail author
  • Yuliang Zhang
  • Satish V. Ukkusuri
  • Rongrong Zhu
Part of the Complex Networks and Dynamic Systems book series (CNDS, volume 4)


Travel behavior plays a crucial role in urban planning and epidemic control. Extensive researches concerning mobile phone data have been performed with the increasing widespread use of mobile phones. However, data sparsity and localization noise pose a great challenge to further studies. In this research, mobile phone call record data (CRD) of 60 days obtained from Shenzhen, China has been put into use. By identifying the home and work location for users, location information for every timeslot was labeled. First, mobility topic was extracted by latent Dirichlet allocation (LDA) model. Then, affinity propagation (AP) was used to analyze users’ mobility patterns from mobility topic distribution. The results revealed that clustering on the level of mobility topic outperformed directly clustering location sequence information. This method could effectively mitigate the adverse impact brought by missing information. Finally, 25 and 17 patterns are found in weekday and weekend, respectively. Representative features were captured from each pattern. By measuring the accuracy of the representative feature, it can be concluded that mobility feature after clustering is capable of describing the main mobility patterns.


Call record data Latent Dirichlet allocation Affinity propagation Mobility pattern 



This research was sponsored by National Natural Science Foundation of China (71171147) and Fundamental Research Funds for the Central Universities.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Chao Yang
    • 1
    Email author
  • Yuliang Zhang
    • 1
  • Satish V. Ukkusuri
    • 1
    • 2
  • Rongrong Zhu
    • 1
  1. 1.School of Transportation Engineering, Key Laboratory of Road and Traffic Engineering of the Ministry of EducationTongji UniversityShanghaiChina
  2. 2.School of Civil Engineering, Purdue UniversityWest LafayetteUSA

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