Interactive visualization of community structure in complex networks

Sammanfattning: Several applied sciences model system dynamics with networks. Since networks often contain thousands or millions of nodes and links, researchers have developed methods that reveal and high- light their essential structures. One such method developed by researchers in IceLab uses information theory to compress descrip- tions of network flows with memory based on paths rather than links and identify hierarchically nested modules with long flow persistence times. However, current visualization tools for navigat- ing and exploring nested modules build on obsolete software that requires plugins and cannot handle such memory networks. Drawing from ideas in cartography, this thesis presents a pow- erful visualization method that enables researchers to analyze and explore modular decompositions of any network. The resulting application uses an efficient graph layout algorithm adapted with a simulation based on information flow. Like in a topographic map, zooming into the map successively reveals more detailed commu- nity structures and network features in a continuous fashion.