System and method for contrastive network analysis and visualization

A non-transitory computer readable medium encoded with instructions for making a computing device execute a method of analyzing a target network relative to a background network of data using machine learning, the method comprising:

• extracting a first feature matrix from an adjacency matrix representative of the target network;
• extracting a second feature matrix from an adjacency matrix representative of the background network;
• generating a projection matrix based on the first and second feature matrices using a contrastive learning algorithm;
• generating a first contrastive matrix representation of the target network based on the projection matrix and the first feature matrix;
• generating a second contrastive matrix representation of the background network based on the projection matrix and the second feature matrix;
• and
• displaying a visualization of unique features of the target network relative to the background network based on the first contrastive matrix and the second contrastive matrix.

A computing device comprising:

• a storage device storing network data associated with a target network and a background network;
• and
• a processor encoded to execute a method of automatically analyzing the target network relative to the background network of data using machine learning, the method comprising:
• extracting a first feature matrix from an adjacency matrix representative of the target network;
• extracting a second feature matrix from an adjacency matrix representative of the background network;
• generating a projection matrix based on the first and second feature matrices using a contrastive learning algorithm;
• generating a first contrastive matrix representation of the target network based on the projection matrix and the first feature matrix;
• generating a second contrastive matrix representation of the background network based on the projection matrix and the second feature matrix;
• and
• displaying a visualization of unique features of the target network relative to the background network based on the first contrastive matrix and the second contrastive matrix.