Graphics Reference
In-Depth Information
Exploring graph data visually is an ideal way to analyze community,
identifying patterns and making observations that would otherwise be very
difficult to detect and understand. Once potentially valuable observations
are discovered and you now know what to look for, you can design targeted
analytics and visualization to confirm those observations across all of the
data.
Techniques for community visualization and analysis for much larger
graphs is a challenge and has been an intense area of research. Approaches
tothisproblemarecoveredinChapter14onBigData,includinghierarchical
community aggregation and summary visualization techniques.
In community analysis, like the examples in this chapter demonstrate, links
very often serve the sole purpose of expressing collective connectedness
in the aggregate. It is not important or even feasible using the techniques
shown so far to understand the character or direction of links. However, in
somedatasets,directionisessential.Chapter12examines flows,illustrating
how you can use graphs to reveal structures and patterns of flow through
linked entities or events.
