1 research outputs found
Mixed coordinate Node link Visualization for Co_authorship Hypergraph Networks
We present an algorithmic technique for visualizing the co-authorship
networks and other networks modeled with hypergraphs (set systems). As more
than two researchers can co-author a paper, a direct representation of the
interaction of researchers through their joint works cannot be adequately
modeled with direct links between the author-nodes. A hypergraph representation
of a co-authorship network treats researchers/authors as nodes and papers as
hyperedges (sets of authors). The visualization algorithm that we propose is
based on one of the well-studied approaches representing both authors and
papers as nodes of different classes. Our approach resembles some known ones
like anchored maps but introduces some special techniques for optimizing the
vertex positioning. The algorithm involves both continuous (force-directed)
optimization and discrete optimization for determining the node coordinates.
Moreover, one of the novelties of this work is classifying nodes and links
using different colors. This usage has a meaningful purpose that helps the
viewer to obtain valuable information from the visualization and increases the
readability of the layout. The algorithm is tuned to enable the viewer to
answer questions specific to co-authorship network studies.Comment: 10 pages, 3 figures, 1 tabl