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A rudimentary piece of Python that derives interesting data from tweets.
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README.md
bad-words.txt
good-words.txt
intensifiers.txt
main.py

README.md

twitter-sentiment-analysis

A rudimentary piece of Python that derives interesting data from tweets.

running

  • Notice the shebang at the top of the main.py script. Be sure this points to your local version of python 3.x.
  • Executing is as easy as ./main.py in your terminal.
  • Be sure to check the paths in main.py. You'll need to supply some json tweets. If you're our professor, we provided them to you. Else, go find some.
  • Enjoy, and check the directory for results.txt.

Be wary of excessively large datasets...

tasks remaining:

  • put together lists of good word, bad words
  • scrub tweets for requested topic, ignoring irrelevant tweets
  • massage tweet text into array of strings (words)
  • actually get score for topic
  • top (5) positive & bottom (5) negative tweets
  • some kind of results report generated
  • optional: figure out hashtag situation
  • optional: add new words to dictionaries
  • for friday: intensifiers
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