Figure 3.

Knowledge and social relatedness. (a) A stylized example of the bipartite PACS-Articles network. (b) The PACS co-occurrence network (monopartite projection on PACS codes). (c) The cosine similarity matrix, which “maps” the physics knowledge space and identifies clusters corresponding to fields. (d) A table illustrating how co-authorship and specialization information are combined to produce the augmented co-authorship network shown in the figure, which includes nodes attributes (specializations). The nodes represent individual scientists (in black) and specializations (in red). Our measure of social relatedness ($S{R}_{\mathit{ib}}$) is defined as a dummy that captures whether scholar i can reach a certain sub-field b through social interactions; $S{R}_{\mathit{ib}}=1$ if $d(i,b)=2$, where d(i, b) is the geodesic distance between scholar i and sub-field b. For instance, $S{R}_{David,45}=1$ since David could directly exchange knowledge with Alice (specialized in sub-field 45), while $S{R}_{David,21}=0$.