  The need to visualize large social networks is growing as hardware
capabilities make analyzing large networks feasible and many new data sets
become available. Unfortunately, the visualizations in existing systems do not
satisfactorily answer the basic dilemma of being readable both for the global
structure of the network and also for detailed analysis of local communities.
To address this problem, we present NodeTrix, a hybrid representation for
networks that combines the advantages of two traditional representations:
node-link diagrams are used to show the global structure of a network, while
arbitrary portions of the network can be shown as adjacency matrices to better
support the analysis of communities. A key contribution is a set of interaction
techniques. These allow analysts to create a NodeTrix visualization by dragging
selections from either a node-link or a matrix, flexibly manipulate the
NodeTrix representation to explore the dataset, and create meaningful summary
visualizations of their findings. Finally, we present a case study applying
NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate
the capabilities of NodeTrix as both an exploration tool and an effective means
of communicating results.
