Week 3

Urban Data - Mobile Phone Data

After working with the census data, this week we will cover how data from mobile phone data is used to study human behavior on urban scales. Our lecture will walk through the different types of data from mobile phones, how to access and process this data, and common considerations when using mobile phone data.

In our practical exercise, we will analyze mobile phone data from Boston and Safegraph to understand how people move around the city and how this data can be used to understand urban dynamics around COVID19 and other problems.

Prepare

📖 Read (at least the first parts about data) some review papers about the use of mobile phone data:

• A review of Urban Computing for Mobile Phone Traces from Marta González and collaborators. [1]

• Mobile phone location data for disasters: A review from natural hazards and epidemics from Takahiro Yabe, Marta Gonzalez and collaborators [2]

• Mobile phone network data for development from UN Global Pulse

• A survey or results on mobile phone datasets analysis by Blondel and collaborators [3]

• Future directions in human mobility science by Luca Pappalardo and collaborators [4]

• Handbook on the Use of Mobile Phone Data for Official Statistics [5]

Participate

🖥️ Lecture 3 – Mobile Phone Data for Urban Science

Perform

⌨️ Lab 3-1 – Working with Location Based Services datasets

Back to course schedule ⏎

References

[1]

S. Jiang, G. A. Fiore, Y. Yang, J. Ferreira Jr, E. Frazzoli, and M. C. González, “A review of urban computing for mobile phone traces: Current methods, challenges and opportunities,” in Proceedings of the 2nd ACM SIGKDD international workshop on urban computing, 2013, pp. 1–9.

[2]

T. Yabe, N. K. Jones, P. S. C. Rao, M. C. Gonzalez, and S. V. Ukkusuri, “Mobile phone location data for disasters: A review from natural hazards and epidemics,” Computers, Environment and Urban Systems, vol. 94, p. 101777, 2022.

[3]

V. D. Blondel, A. Decuyper, and G. Krings, “A survey of results on mobile phone datasets analysis,” EPJ Data Science, vol. 4, no. 1, p. 10, Dec. 2015, doi: 10.1140/epjds/s13688-015-0046-0.

[4]

L. Pappalardo, E. Manley, V. Sekara, and L. Alessandretti, “Future directions in human mobility science,” Nature Computational Science, vol. 3, no. 7, pp. 588–600, Jul. 2023, doi: 10.1038/s43588-023-00469-4.

[5]

U. ESCAP, “Handbook on the use of mobile phone data for official statistics,” 2019.