Network construction: We use the degree of overlap in reference lists to construct a network of all articles in our corpus (a technique called bibliographic coupling). If two articles have non-overlapping reference lists, they are not linked; if they have identical references, the strength of their connexion is maximal. The network is dynamic because a moving time window with a length of five years slides through time, one year at a time, starting with window 1956- 1960, then moving to 1957-1961 and so on until the end of our period in 2010-2014. This definition of our network means that two documents that have been published more than five years apart are in the same overall network, but never appear jointly in a time window.
Cluster detection: In each time window, an algorithm for community detection based on modularity optimization is applied to the current state of the network. The algorithm used is a variation on the Louvain method. The panel depicting linked circles is a representation at the level of these communities (not of the underlying documents). Once we have community assignments for each window, basic rules based on proximity of clusters from one time window to the next are applied to determine whether a cluster survives, splits, merges or dies without leaving a trace. These rules generate the polygons (i.e. the specialties) that stretch from the beginning to the end of our period in the first panel.
Keywords retrieval: Keywords represent the words that most characteristically distinguish the titles of the articles in the relevant cluster from articles in the other clusters. The panel with polygons gives keywords for each cluster over its full lifetime. The panel with linked circles gives time-specific keywords. These keywords slowly change through time as a specialty changes its focus.
This project was made possible by the generous support of the History of Economics Society and the Université de Sherbrooke. François Claveau was project leader, Till Düppe and Yves Gingras acted as advisors. We are grateful to Saad Blakime and Timothy D. Bowmans for programming the web application.