Readings Due: 

• Davis, Dorian Hunter and Aram Sinnreich. “Beyond Fact-Checking: Lexical patterns as Lie Detectors in Donald Trump’s Tweets.” International Journal of Communication. 14 (2020), 5237-5260. 
• D’Agnosio, Catherine and Lauren Klein. “What Gets Counted Counts.” Data Feminism. Cambridge, MA: MIT Press, 2020. https://data-feminism.mitpress.mit.edu/pub/h1w0nbqp/release/2?readingCollection=0cd867ef 
• Jiang, Allen. “AI Ethics: Identifying Your Ethnicity and Gender”  https://medium.com/towards-artificial-intelligence/does-a-machine-know-your-gender-based-on-your-tweets-43b14740fd54 Medium. Accessed 10/27/2020. 
• Spend time exploring the following projects. What can you learn about their research question, data, and conceptualization? Are the data and the questions appropriately matched? What features of the dataset were selected to create the analysis? Is the method of measurement meaningful? 
  • Gender in Rate Your Professor: including the associated blog post. 
  • Dialogue in Disney Movies, by The Pudding
  • Gender Analyzer: https://app.readable.com/text/gender/ 

Notebook Activity:

Text Classification task: TBD

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