  For decades, researchers in information visualisation and graph drawing have
focused on developing techniques for the layout and display of very large and
complex networks. Experiments involving human participants have also explored
the readability of different styles of layout and representations for such
networks. In both bodies of literature, networks are frequently referred to as
being 'large' or 'complex', yet these terms are relative. From a human-centred,
experiment point-of-view, what constitutes 'large' (for example) depends on
several factors, such as data complexity, visual complexity, and the technology
used. In this paper, we survey the literature on human-centred experiments to
understand how, in practice, different features and characteristics of
node-link diagrams affect visual complexity.
