Brief project description: With the help of the Davidson Hate Speech data set, we created and trained a classification model to successfully identify hate speech and placed it into a Twitter-Bot to perform a case study in a real-world environment.
Pythonversion: Predominantly the python-version 3.8 was used, however most of the Python 3 versions should work.
Libraries and Versions: Tensorflow Version: 2.7 Pandas Version: 1.3 Numpy Version: 1.21 Scikit-learn Version: 1.0 Nltk Version: 3.6 Keras Version: 2.7 Matplotlib Version: 3.5 Itertools Basic Part of Python
Installation manual: Install anaconda Create new Anaconda environment Install CMD.exe in Anaconda environment Install Jupyter Notebook in Anaconda environment Open the prompt and execute the following commands pip install pandas pip install numpy pip install scikit-learn pip install tensorflow pip install nltk pip install keras pip install matplotlib
Open the Jupyter python notebook and run „Hate Speech.ipynb“.
Installing the Twitter Bot:
To install the Bot you have to perform the following to tasks on the command prompt using your python environment
- python main.py install
- python main.py build
Run the Twitter Bot:
To start the Twitter Bot, navigate into the Project Folder "Hate Speech" Open up a console in this directory activate your conda environment (conda activate [environment name]) type in python main.py build and run:
- python main.py
To talk with the bot you have to open the conversation and you are getting greeted by the bot. The bot then tells you what to do.