New ideas for measuring reputation based on graph neaural nets.
An example of how to use the tools here is present in main.py
.
Reddit data is avaliable at https://files.pushshift.io/reddit/comments/
The setup for GloVe embeddings follows from this tutorial: https://medium.com/@martinpella/how-to-use-pre-trained-word-embeddings-in-pytorch-71ca59249f76
- Download the word vectors glove.6B.zip from: https://nlp.stanford.edu/projects/glove/
- Extract the zip folder contents into
machine_learning/glove
- run
cd machine_learning && python create_glove_embedding.py
. This will process the word vectors and save the results into pkl files.
- if not done already, run
pip install -r requirements.txt
- run
python process_trees.py
. This creates a pickle file of 100 processed trees - cd to
machine_learning
and runpython glove_gat.py
. This trains the model on the pickle file just created