Recommended Resources

Here are some resources that I believe to be useful, and I find some of them particularly insightful or informative! I listed the information relevant to my research topics at first. Other resources, including those about fundamental subjects, are listed at the end.

Algorithmic Fairness

• Barocas, Solon and Moritz Hardt and Arvind Narayanan. 2019. Fairness and Machine Learning. fairmlbook.org. http://www.fairmlbook.org
• Kearns, Michael, and Aaron Roth. 2019. The ethical algorithm: The science of socially aware algorithm design. Oxford University Press.

Computational Social Science

• Cioffi-Revilla, Claudio. 2014. Introduction to computational social science. Springer.
• Nelimarkka, Matti. 2020. CODING SOCIAL SCIENCE: Understanding and Doing Computational Social Science codingsocialscience.org. http://codingsocialscience.org
• Salganik, Matthew J. 2019. Bit by bit: Social research in the digital age. Princeton University Press.

Network Science

• Newman, Mark. 2018. Networks. Oxford university press.

Other Resources

For Learners with Appropriate Background

• Kadushin, Charles. 2012. Understanding social networks: Theories, concepts, and findings. Oxford University Press.

See also the complete list of recommended resources for learners with appropriate background.

For General Audiences

• Kearns, Michael, and Aaron Roth. 2019. The ethical algorithm: The science of socially aware algorithm design. Oxford University Press.
• Johnson, Allan G. 1997. The forest and the trees: Sociology as life, practice, and promise. Temple University Press.
  • Johnson, Allan G. 著，成令方、林鶴玲、吳嘉苓譯，2001，見樹又見林：社會學作為一種生活、實踐與承諾。群學。

See also the complete list of recommended resources for general audience.