Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

TDM Studio

Sentiment Analysis Data Visualization

Sentiment Analysis or Affect Classification can be valuable for lots of different research and learning objectives. Some common questions which researchers often explore using Sentiment Analysis include:

  • What public emotions drive successful presidential campaigns? Social control and power are driven by which emotions? Do U.S. presidents win elections with fear or anger or love?
  • How does public sentiment about a company (e.g. Tesla or GameStop), as reported by newspapers, relate to company stock price over time? 
  • What is the long-term emotional impact of collective trauma? How does public sentiment change (and recover?) in response to tragic events?  

For this documentation walkthrough, we will specifically be looking at one month of newspaper coverage for September 2001. How does collective emotion, as expressed in a newspaper such as The New York Times change and respond following a tragic event such as the September 11, 2001 terrorist attack? We create a dataset of the 8851 newspaper articles which were published for the month of September 2001 from The New York Times.