This project started as a way to practice with pythons NLTK but with the last presidential election and the current president's love of this medium, it has morphed into a much greater analysis tool. I am looking to gather tweets not written by the people below, but more about the people below.

The main idea here is to get a feeling for how the twitter-verse feels about the United States government, to do this politikweet tracks the keywords below in the public twitter stream capturing tweets, politikweet will then follow any embedded links and analyze for sentiment, both the tweet and any underlying content; the funny thing is that content can be written with positive sentiment on despicable subjects.

This is an exercise in Natural Language Processing. So that we can gain emotional insights from the written word.

Twitter can tell us a lot about how the world feels about the current administration and has become a bell weather for tracking reputation, so lets track the key words below and see how the twitter-verse feels about our government.

Keywords in the twitter stream

  • President
  • Congress
  • Senate
  • White House
  • Supreme Court
  • Politics
  • Political
  • Demagogue
  • House Of Representatives
  • Department Of Agriculture
  • Department Of Commerce
  • Department Of Defense
  • Department Of Education
  • Department Of Health And Human Services
  • Department Of Homeland Security
  • Department Of Housing And Urban Development
  • Department Of Energy