jdc08161063 / counteract

Fighting mental illness through ML

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.

##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 :)

##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.