Document co-citation analysis to enhance transdisciplinary research

Abstract

Specialized and emerging fields of research infrequently cross disciplinary boundaries and would benefit from frameworks, methods, and materials informed by other fields. Document co-citation analysis, a method developed by bibliometric research, is demonstrated as a way to help identify key literature for cross-disciplinary ideas. To illustrate the method in a useful context, we mapped peer-recognized scholarship related to systems thinking. In addition, three procedures for validation of co-citation networks are proposed and implemented. This method may be useful for strategically selecting information that can build consilience about ideas and constructs that are relevant across a range of disciplines.

Fig. 1. DCA.

DCA illustration of the conversion of citation data (A) to a co-citation network (B) and the resulting node (C) and edge (D) metrics before and after trimming (E).

Fig. 2. Systems thinking document co-citation network.

Results trimmed at the following co-citation frequency levels: (A) ≥3, (B) ≥5, (C) ≥7, and (D) ≥9. A key is provided in the lower right panel (E). Nodes represent co-cited documents with top co-cited documents among a community labeled by author(s) and year published. Node shape and color represent assigned community determined by smart local moving (SLM) detection for each network. Edges represent co-citations between documents with frequencies represented by width and color tone. Communities in the ≥3 network of fewer than three documents were not included in the visual because these four small communities were complete and isolated. Visualization was made with organic layout in Cytoscape (34).

Fig. 3. Subjects of co-citation communities.

The top three WorldCat subject labels are shown for each of the main communities. The color, shape, and bolded number correspond to the co-citation communities in the ≥3 systems thinking network in Fig. 2A. Numbers of co-cited documents within each community that have a topic label are reported.

Fig. 4. Comprehensive co-citation network.

A co-citation network generated from comprehensive search criteria with edges trimmed to frequencies of three or more co-citations. Documents matching those in the ≥3 systems thinking network of Fig. 2A are colored blue. Top co-cited documents from Table 1 are labeled.