Utilizing digital traces of mobile phones for understanding social dynamics in urban areas

Oded Zinman, Boaz Lerner

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Understanding land use in urban areas, from the perspective of social function, is beneficial for a variety of fields, including urban and highway planning, advertising, and business. However, big cities with complex social dynamics and rapid development complicate the task of understanding these social functions. In this paper, we analyze and interpret human social function in urban areas as reflected in cellular communication usage patterns. We base our analysis on digital traces left by mobile phone users, and from this raw data, we derive a varied collection of features that illuminate the social behavior of each land use. We divide space and time into basic spatiotemporal units and classify them according to their land use. We categorize land uses with a leveled hierarchy of semantic categories that include different levels of detail resolution. We apply the above methodology to a dataset consisting of 62 days of cellular data recorded in nine cities in the Tel Aviv district. The methodology proved beneficial with an accuracy rate ranging from 84 to 91%, dependent on land use label resolution. In addition, analyzing the results sheds light on some of the limitations of relying solely on cellular communication as a data resource. We discuss some of these problems and offer applicable solutions.

Original languageEnglish
Pages (from-to)535-549
Number of pages15
JournalPersonal and Ubiquitous Computing
Issue number4
StatePublished - 1 Aug 2020


  • Classification
  • Computational social science
  • Land use
  • Mobile phone data
  • Smart cities
  • Urban computing

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Science Applications
  • Management Science and Operations Research


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