This repository implements Text GCN, a graph-based deep learning approach to text classification where documents and words are represented as nodes in a unified graph. The model learns embeddings by applying graph convolutional operations over the word-document co-occurrence graph. It supports multiple benchmark datasets (20ng, R8, R52, ohsumed, mr) and uses TensorFlow for implementation.