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.
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.”
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.
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.