We are launching Graph Viz 101, a series of posts to teach the basics of graph visualization, written by Sébastien Heymann in collaboration with Bénédicte Le Grand of Université de Paris 1. This is our second post, please discuss it below!
Information visualization has been used to support social network analysis since the 1930s with the “sociogram” of J. Moreno (Moreno 1937), which is a graphic representation of social ties among a group of people. Despite the early beginning of network visuals, we had to wait until the 1990s and the democratization of computer graphics to see the development of interactive visualization software, which has made the interactive exploration of complex networks possible. Pajek (Batagelj 1998) is the most noticeable tool, as it provides both statistical algorithms and visual representations of social networks. Its methodological book entitled “Exploratory Social Network Analysis with Pajek” was published in 2005. The contribution of Information Visualization to science is stated in (Fekete 2008):
Information Visualization is meant at generating new insights and ideas that are the seeds of theories by using human perception as a very fast filter: if vision perceives some pattern, there might be a pattern in the data that reveals a structure. […] Therefore, it plays a special role in the sciences as an insight generating method.