ISN: Network visualisation

Today’s topic will be to visualise networks and centrality measures. We visualise a network to better understand the underlying data. A visualisation should be driven by the question that we would like to answer. Nonetheless, visualisations are by their nature exploratory. Also, visualisations do not provide evidence for hypothesis.

Visualisation usually tries to convey information by the layout. Density tries to convey cohesion. Distance tries to convey graph-theoretic distance, tie length tries to convey attached values. Geometric symmetries try to convey structural symmetries.

General rules of graph visualisation is that no edge crossing, overlap, asymmetry or meaningless edge ledge/node side should occur.

Visualisation in R

We will use either the “igraph” or “sna” library to visualise the data.