Matrices
Last updated
Last updated
Matrices are another way to visualize network data.
This is done using an adjacency matrix.
The nodes are encoded using rows and columns, and the edges are encoded in the cells.
Full visibility of nodes and relationships, and corresponding properties
No line crossings (so, no clutter)
This gets rid of the hairball effect that is common in node-link diagrams, especially when every node is connected to every other node:
Less familiarity with the representation, since it isn't very common
Feels less natural than using nodes and links
Less scalability (cells become too small beyond 100-200 nodes)
Needs reordering in order to show structures or patterns
For undirected networks, matrices are symmetric. However, for directed networks, the cells can be filled according to the edge directions.
Left: without sorting the data, Right: after sorting the data
A parallel axes representation is a common substitute for matrices, when direction is to be shown:
