UC Santa Cruz
Methods for Visually Exploring Large and Complex Networks
- Author(s): Cesario, Nathaniel E.
- Advisor(s): Pang, Alex
- et al.
Most graph layout algorithms strive to present an uncluttered view of the graph
that reflects the structural relationship between nodes and edges comprising the
graph. Very few focus on providing a layout based on either node or edge
attribute values. This thesis presents a method that can reflect
structural information, be influenced primarily by attribute values of graph
elements, or some combination of both. This is achieved using a force-based
graph layout strategy and force transfer functions--a flexible graph layout
specification that alters forces depending on attribute values or structural
information. An immediate benefit of this flexibility is the
ability to perform visual clustering via the resulting graph layouts.
As graphs get larger and more complex, the flexibility for exploring different
relational properties of graph elements will allow us to understand them better.
As an example, this technique is used to group left and right blogs as well as detect outliers
in a political blog dataset.