Crossmaps: Visualization of overlapping relationships in collections of journal papers

Abstract

A crossmapping technique is introduced for visualizing multiple and overlapping relations among entity types in collections of journal articles. Groups of entities from two entity types are crossplotted to show correspondence of relations. For example, author collaboration groups are plotted on the x axis against groups of papers (research fronts) on the y axis. At the intersection of each pair of author group/research front pairs a circular symbol is plotted whose size is proportional to the number of times that authors in the group appear as authors in papers in the research front. Entity groups are found by agglomerative hierarchical clustering using conventional similarity measures. Crossmaps comprise a simple technique that is particularly suited to showing overlap in relations among entity groups. Particularly useful crossmaps are: research fronts against base reference clusters, research fronts against author collaboration groups, and research fronts against term co-occurrence clusters. When exploring the knowledge domain of a collection of journal papers, it is useful to have several crossmaps of different entity pairs, complemented by research front timelines and base reference cluster timelines.

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Stored only when both papers are in the corpus — 56 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.