14. Awesome extensions

So many topics, so little time. A short survey on some of the many many topics we could have covered but didn’t.

Figure 1: Artwork by @allison_horst.

Agenda

December 7, 2021

1. Return clickers
2. What’s next
3. Course Evaluations

Readings

• Class notes: Extensions

• Silge and Robinson (2021), Text Mining with R.

Reflection questions

• What do I love most about the methods we’ve been covering? The math? The statistics? The programming? The algorithms? The data? The ethical quandaries?

• The whale shark above is a graphic meant to help understand principal components. Yet one more thing we didn’t touch on, but could have.

Ethics considerations

• Keeping asking yourself:

  • How do I stay accountable for my work?
  • How might others be impacted by what I’ve created?
  • Where did the data come from, and what biases might be inherent?
  • What population is appropriate for any of the inferential claims I’m making?
  • How might individual’s privacy or anonymity be impacted by what I’ve created?
  • Is it possible that my work could be misinterpreted or misused?

Slides

• In class slides - extensions for 12/07/21.

Additional Resources

• Julia Silge’s blog many string examples

• Nate Silver and Galen Druke of 538 talk about the problems with using sentiment analysis to measure whether the mainstream media is more biased against Biden or Trump. Is The Media Tougher On Biden Than Trump?