Awesome

Twitter Sentiment Analysis Model

What is this repo?!

• A model build for Twitter Sentiment analysis, P file and H5 file included
• The Python 3 code to build the above model using Keras, Theano & Pandas

I was set the task to try and make a sentiment analysis model for Twitter for my dissertation even though the due by date is long past I still wanted to accomplish this task.

For my dissertation I was set the task to predict stock prices for a single company on the stock market using Twitter and sentiment analysis. I tried to see if you could predict if the stock market would go up or down given the sentiment of the Tweets.

Dependancies

This model uses a number of open source projects to work properly:

• Keras - A Machine Learning Neural Network front end framework
• Theano - A Machine Learning Neural Network back end framework (For Keras)
• Pandas - A Python dataframe library
• [Pickle] - A Python serilisation lib, I use this to serialise the Tokenier with all the word mappings in
• [RE] - Regular expressions are not used in the version but left the method in for removing hyperlinks, at and hashtag symbols

Training Info

I used a Cuda on a Nvidia 960M it took about 4 hours/ish for 10 epochs of 900,000 Tweets, Every 100,000 Tweets testing using 10,000 Tweets is done.

Model Info

This model is 79% accurate and has 0.41 loss. If you want to use remember to deseralise the Keras tokenier which is the *.p file the tokenizer ahs a 100,000 unique word count, the predict.py has an example. Here is a small example of the model output:

Free Software, Hell Yeah!