Analyzing data provided in https://snap.stanford.edu/data/higgs-twitter.html, using techniques described in https://ojs.aaai.org/index.php/ICWSM/article/view/22193.
To manage repository size, the non-retweet data has been excluded. We can look into Git Large File Storage (LFS) to include these in the repository, if necessary.
To check DeepGL documentation, go to https://htmlpreview.github.io/?https://github.com/takanori-fujiwara/deepgl/blob/master/doc/index.html
To run:
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Run
docker build -t tiagopeixoto/graph-tool .to build a Docker container containing all of this project's dependencies.- Command should be executed in the same directory as the dockerfile.
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To enter a terminal for the newly built container, run
docker run --interactive --tty --rm --mount type=bind,source="C:File path to current directory"/,target=/your_code --workdir=/your_code tiagopeixoto/graph-tool bash -
From this terminal, preprocess the data and generate node embeddings with
python3 generate_embeddings.py. -
From this terminal, perform classifications based on the node embeddings with
python3 classification.py.