Andrew Li (Pd. 1) and Justin Li (Pd.5)
Our project is a bot that automatically scrapes and analyzes messages sent on the Discord messaging platform. The bot will use a machine learning algorithm to detect the “sentiment”, or overall positivity or negativity, of messages sent through the platform. We will train the bot’s algorithm using datasets available online. The machine learning algorithm will use a process called word embedding which reduces every word into a multi-dimensional vector, representing the overall “profile” of the word (similar words will have similar directions and magnitudes in its vector representation).
The purpose of this bot is to provide a platform for positive environment control. This framework could be used to direct online discussion on sites like Facebook or Twitter in a positive direction or be used by businesses to promote positive interaction between automated customer service bots and customers.
Tensorflow and Tensorboard (1.8.0)
NumPy
Discord.py
If you do not have Python 3.6.x 64 bit installed, install it from www.python.org/downloads/release/python-365/
When installing, make sure to choose "Add Python 3.6 to PATH" on the first screen. Also choose to disable PATH length limit at the end of installation.
Download this repository from GitHub as a ZIP file and extract all. In the extracted folder, navigate to the
/CS-Final-2018-master/Data/ folder and extract the ids_matrix.npy.zip file to /CS-Final-2018-master/Data/.
Make sure you do NOT not extract to a new folder named ids_matrix.npy If you do, move the ids_matrix.npy file
inside the folder of the same name outside to /CS-Final-2018-master/Data/.
Run command prompt in administrator mode and run the following line:
pip install tensorflow
Navigate in command prompt to /CS-Final-2018-master/Bot and run the following line:
python analyze_sentiment.py
The script may take a few moments to load. Ignore any non-fatal warnings. The console will print the results of the test of the neural network. After the tests finish, you may enter any input you want to test the network.
The output will list a positive score, which represents how positive the message is, and a negative score, which represents how negative the message is. The composite score is the difference of the positive score and the negative score. A positive composite score represents a positive message and vice-versa.
An error may ask you install Microsoft Visual C++ Redistributable 2015. Follow any error messages and run the script again.