Key readings

All lecture slides include a reference list. Please go through these materials.

A indicative list of key readings include:

Also, the Big Book of R is a great collection of R related books. Some of these include:

Please don’t limit your reading in the following list.

For those who want to explore the networks further

Key readings

Barabási, Albert-László. 2016. Network Science by Albert-László Barabási. Cambridge: Cambridge University Press. http://networksciencebook.com/.
Batty, Michael. 2013. The New Science of Cities. MIT press.
Bauer, P. C., Landesvatter C., and L. Behrens. 2022. “APIs for Social Scientists: A Collaborative Review V1.0.” https://doi.org/https://doi.org/10.5281/zenodo.6798690.
Bettencourt, Luı́s MA. 2021. “Introduction to Urban Science: Evidence and Theory of Cities as Complex Systems.”
Boehmke, Brad, and Brandon Greenwell. 2019. Hands-on Machine Learning with r. Chapman; Hall/CRC.
Light, Ryan, and James Moody. 2020. The Oxford Handbook of Social Networks. Oxford University Press.
Lovelace, Robin, Jakub Nowosad, and Jannes Muenchow. 2019. Geocomputation with r. Chapman; Hall/CRC.
Neal, Zachary P, and Céline Rozenblat. 2021. Handbook of Cities and Networks. Edward Elgar Publishing.
Rodrigue, Jean-Paul. 2020. The Geography of Transport Systems. Routledge. https://transportgeography.org/.
Singleton, Alex D, Seth Spielman, and David Folch. 2017. Urban Analytics. Sage.
Wickham, Hadley. 2016. “Data Analysis.” In Ggplot2, 189–201. Springer.
Wickham, Hadley, and Garrett Grolemund. 2016. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. " O’Reilly Media, Inc.".
Xie, Yihui, Christophe Dervieux, and Emily Riederer. 2020. R Markdown Cookbook. Chapman; Hall/CRC.