This project creates a graph of New York Times Articles (node), Users (node), and user's comments (relationships). The data was taken from kaggle: see New York Times Comments.

The data contains information about the comments made on the articles published in New York Times in Jan-May 2017 and Jan-April 2018. The month-wise data is given in two csv files - one each for the articles on which comments were made and for the comments themselves. The csv files for comments contain over 2 million comments in total with 34 features and those for articles contain 16 features about more than 9,000 articles.

Running this project will start 2 services:

Neo4J Graph @ http://localhost:7474	Toy Recommender @ http://localhost:5000

git
docker
docker-compose

Note: Downloading our dataset (via setup.sh) uses kaggle API credentials stored in ~/.kaggle/kaggle.json. See API Credentials from the kaggle-api docs.

git clone https://github.com/jvani/nyt-comments.git && \
  cd nyt-comments && \
  ./setup.sh

The setup.sh script will do the following:

1. Pull used docker images.
2. Download neo4j plugins (written to $PWD/plugins)
3. Download our dataset (written to $PWD/kaggle/)
4. Create our graph data (written to $PWD/import)
5. Import our data into neo4j (database files will be written to $PWD/data)
6. Start our docker-compose services: neo4j and toy recommender. NOTE: a jupyter server is included but the image is HUGE and off by default; uncomment in the docker-compose.yaml if desired.
7. Run graph statistics on our database.