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Counteract

Welcome to the repository for Counteract, a crowdsourced risk analysis platform for sending nice messages to people who may be having a bad day or show signs of mental illness. This project will soon be made open source.

##Info: We utilized SVM Classification on public tweets to classify tweets as happy/sad, then a Markov chain on encouraging tweets to generate a happy message to tweet at the person who tweeted something sad.

##Demo: The following tweets are 100% generated through our system with no human interference :) pic1 pic2 pic3

##File Importance:

  • posts.txt - A list of tweets we mined with a tweet on each line

  • classify.txt - A list of classifications corresponding to posts.txt that we classified as happy/sad

  • encouraging.txt - A list of encouraging messages/quotes that we used to train the Markov chain

  • requirements.txt - A list of Python requirements required to run our project, along with Scikit-Learn and Numpy

  • gettweets.py - Our tweet mining file that saved the tweets into posts/classify.txt

  • nlp1.py - Our original text classification engine courtesy of Patrick Demichele

  • index.py - Our main Python file that streams tweets and generates responses to the sad tweets.

Contributors

The following individuals are currently contributing to Counteract: Jay Shenoy, Andy Kamath, Patrick DeMichele, Karan Kanwar, Kelsey Nieman, Matt Zhou, Michelle Huang, and Rufus Behr.

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