Week 4

Urban Data - Social Media Data / Ethics

This week we will see how data from social media is used human behavior on urban scales. We will focus on geo-located data from traditional social media (Facebook, Twitter/X) but also from Location-Based Social Networks (Foursquare, Yelp, etc).

We will also discuss the ethical implications of using private sensitive data in urban science research.

In our practical exercises, we will analyze social media data from Gowalla and Facebook to understand the interplay between social networks and geography in urban areas.

Prepare

📖 Read some review papers about the use of social media data for urban science, and Chapter 6 of Salganik’s book about Ethics in Computational Social Science:

• Social-media data for urban sustainability [1]

• Social media data: Challenges, opportunities and limitations in urban studies [2]

• The Role of Space in the Formation of Social Ties [3]

• Friendship and Mobility: user movement in Location-Based Social Networks [4]

• Social Connectedness: Measurement, Determinants, and Effects [5]

• Chapter 6 of Bit by Bit book by Salganik [6]

Participate

🖥️ Lecture 4 –Social Media Data for Urban Science

🖥️ Lecture 5 - Ethical considerations in Computational Urban Science

Perform

⌨️ Lab 4-1 – Social media data: relationship between mobility and social connections

⌨️ Lab 4-2 – Using social media data to understand Geographical social networks

Back to course schedule ⏎

References

[1]

R. T. Ilieva and T. McPhearson, “Social-media data for urban sustainability,” Nature Sustainability, vol. 1, no. 10, pp. 553–565, Oct. 2018, doi: 10.1038/s41893-018-0153-6.

[2]

P. Martí, L. Serrano-Estrada, and A. Nolasco-Cirugeda, “Social Media data: Challenges, opportunities and limitations in urban studies,” Computers, Environment and Urban Systems, vol. 74, pp. 161–174, Mar. 2019, doi: 10.1016/j.compenvurbsys.2018.11.001.

[3]

M. L. Small and L. Adler, “The Role of Space in the Formation of Social Ties,” Annual Review of Sociology, vol. 45, no. Volume 45, 2019, pp. 111–132, Jul. 2019, doi: 10.1146/annurev-soc-073018-022707.

[4]

E. Cho, S. A. Myers, and J. Leskovec, “Friendship and mobility: User movement in location-based social networks,” in Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, in KDD ’11. New York, NY, USA: Association for Computing Machinery, Aug. 2011, pp. 1082–1090. doi: 10.1145/2020408.2020579.

[5]

M. Bailey, R. Cao, T. Kuchler, J. Stroebel, and A. Wong, “Social Connectedness: Measurement, Determinants, and Effects,” Journal of Economic Perspectives, vol. 32, no. 3, pp. 259–280, Aug. 2018, doi: 10.1257/jep.32.3.259.

[6]

M. J. Salganik, Bit by bit: Social research in the digital age. Princeton University Press, 2019.