NATURAL LANGUAGE PROCESSING 

> > I’M > > ___ ___ _____ _____ ___ _ _ > | \/ || ___| __ \ / _ \ | \ | | > | . . || |__ | | \// /_\ \| \| | > | |\/| || __|| | __ | _ || . ` | > | | | || |___| |_\ \| | | || |\ | > \_| |_/\____/ \____/\_| |_/\_| \_/ > > _____ ______ _____ _____ ______ > / ___|| ___ \| ___|_ _|| ___ \ > \ `--.|| |_/ /| |__ | | || |_/ / > `--. \| __/ | __| | | || / > /\__/ /| | | |___ _| |_|| |\ \ > \____/ \_| \____/ \___/ \_| \_| > > > [email protected] > > > > > 

MORGAN 

PROBLEM? What did people really think about my event? Discover the truth with Morgan’s Twitter Sentiment Analysis 

NAÏVE BAYES CLASSIFIER A Naïve Bayesian classifier assumes probabilities being combined are independent of each other. Not true considering python (the snake) and python (the language) mean different things given the context. 

To make up for its naïveté, calculate the probability of a tweet being in a specific category by multiplying together all the probabilities
of the individual words in a tweet. Love Hate Excited Bored 0 20 40 60 80 Negative Positive 

EXAMPLES Positive: #FBGGD Negative: #McDstories Neutral: @jack 

THE STACK Python, Flask, PostgreSQL, nginx, uWSGI, Twitter API Bootstrap, CSS, Javascript, D3.js 

CHALLENGES The Twitter API Humans 

RESOURCES You can do it too! ! http.www.laurentluce.com/posts/
 twitter-sentiment-analysis-using-python-and-nltk 

> > > > _____ _ _ ___ _ _ _ __ > |_ _| | | | / _ \ | \ | || | / / > | | | |_| |/ /_\ \| \| || |/ / > | | | _ || _ || . ` || \ > | | | | | || | | || |\ || |\ \ > \_/ \_| |_/\_| |_/\_| \_/\_| \_/ > > __ _______ _ _ > \ \ / / _ | | | | > \ V /| | | | | | | > \ / | | | | | | | > | | \ \_/ / |_| | > \_/ \___/ \___/ > > > [email protected] > > > > Copyright © 2013 Megan Speir. All rights reserved. >