  Existing dynamic weighted graph visualization approaches rely on users'
mental comparison to perceive temporal evolution of dynamic weighted graphs,
hindering users from effectively analyzing changes across multiple timeslices.
We propose DiffSeer, a novel approach for dynamic weighted graph visualization
by explicitly visualizing the differences of graph structures (e.g., edge
weight differences) between adjacent timeslices. Specifically, we present a
novel nested matrix design that overviews the graph structure differences over
a time period as well as shows graph structure details in the timeslices of
user interest. By collectively considering the overall temporal evolution and
structure details in each timeslice, an optimization-based node reordering
strategy is developed to group nodes with similar evolution patterns and
highlight interesting graph structure details in each timeslice. We conducted
two case studies on real-world graph datasets and in-depth interviews with 12
target users to evaluate DiffSeer. The results demonstrate its effectiveness in
visualizing dynamic weighted graphs.
