GraphNN

Dataset Info

This webgraph is a page-page graph of verified Facebook sites. Nodes represent official Facebook pages while the links are mutual likes between sites. Node features are extracted from the site descriptions that the page owners created to summarize the purpose of the site. This graph was collected through the Facebook Graph API in November 2017 and restricted to pages from 4 categories which are defined by Facebook. These categories are: politicians, governmental organizations, television shows and companies. The task related to this dataset is multi-class node classification for the 4 site categories.

PART A:

1. Creation of nodes and edges in the graph
2. Visualisation
3. Finding Clustering Coefficients, Degree, Pagerank etc...
4. Community detection
5. Generate inferences from all the above attributes.

PART B:
Create a Graph neural network and complete the following:

1. Link prediction
2. Node classification

Use 70-30 train test split, take random seed = 42

Metrics Accuracy to be generated as it will be graded based on the metrics itself.

Minimum Requirements

 networkx          2.4
 tqdm              4.28.1
 numpy             1.15.4
 pandas            0.23.4
 texttable         1.5.0
 scipy             1.1.0
 argparse          1.1.0
 gensim            3.6.0

Installation commands if needed

 pip intall jupyternotebook
 pip intall networkx
 pip intall pytorch
 pip install torch-geometric
 pip install -q torch-scatter -f https://data.pyg.org/whl/torch-1.10.0+cu113.html
 pip install -q torch-sparse -f https://data.pyg.org/whl/torch-1.10.0+cu113.html
 pip install -q git+https://github.com/pyg-team/pytorch_geometric.git
 pip install --upgrade torch-cluster

Repository Handlers
Arnav Kumar
Vijith BG