Graph neural networks apply the predictive power of deep learning to rich data structures that depict objects and their relationships as points connected by lines in a graph. In GNNs, data points are called nodes, which are linked by lines -- called edges -- with elements expressed mathematically so machine learning algorithms can make useful predictions at the level of nodes, edges or entire graphs. An expanding list of companies is applying GNNs to improve drug discovery, fraud detection and recommendation systems. These applications and many more rely on finding patterns in relationships among data points. Social media has become one of the largest epidemics in the World.