If you are having difficulty thinking of a book to review for the course, you could select one from the following list:
Bulson, Eric Jon. Ulysses by Numbers. Columbia University Press, 2020. cuny-gc.primo.exlibrisgroup.com, https://doi.org/10.7312/buls18604.
Criado-Perez, Caroline. Invisible Women: Data Bias in a World Designed for Men. Abrams Press, 2019.
Chun, Wendy Hui Kyong. Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition. The MIT Press, 2021.
Chun, Wendy Hui Kyong. Updating to Remain the Same. MIT Press, 2017, https://mitpress.mit.edu/books/updating-remain-same.
Gavin, Michael. Literary Mathematics: Quantitative Theory for Textual Studies. Stanford University Press, 2022.
Guyan, Kevin. Queer Data: Using Gender, Sex and Sexuality Data for Action. Bloomsbury Academic, 2022, https://www.bloomsbury.com/us/queer-data-9781350230729/.
Gittleman, Lisa. Raw Data Is an Oxymoron. 2013. direct.mit.edu, https://doi.org/10.7551/mitpress/9302.001.0001.
So, Richard Jean. Redlining Culture: A Data History of Racial Inequality and Postwar Fiction. Columbia University Press, 2020, p. 240 Pages.
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