The Structure and Dynamics of Scientific Knowledge - Mapping Scientific Frontiers: The Quest for Knowledge Visualization - page 178

identify a specialty? They used concepts such as “cognitive coherence” within
clusters and “cognitive differences” between clusters. Their results suggested that
co-citation analysis indeed showed research specialties, although one specialty may
be fragmented across several different clusters. They concluded that co-citation
clusters were certainly not artifacts of an applied technique. On the other hand, their
study suggested that co-citation clusters did not represent the entire body of publi-
cations that comprised a specialty. Therefore, they concurred the recommendation
of Mullins et al. ( 1988 ) that it would be necessary to analyze different structural
aspects of publications so as to generate significant results in science mapping.

5.3.2 Author Co-Citation Analysis

The 1980 s saw the beginning of what turned out to be a second fruitful line of
development in the use of citation to map science - author co-citation analysis
(ACA). Howard White and Belver Griffith introduced ACA in 1981 as a way to
map intellectual structures (White and Griffith 1981 ). The unit of analysis in ACA is
authors and their intellectual relationships as reflected through scientific literatures.
The author-centered perspective of ACA led to a new approach to the discovery
of knowledge structures in parallel to approaches used by document-centered co-
citation analysis (DCA).

5.3.2.1 Intellectual Structures

An author co-citation network offers a useful alternative starting point for co-citation
analysis, especially when we encounter a complex document co-citation network,
and vice versa. Katherine McCain ( 1990 ) gave a comprehensive technical review of
mapping authors in intellectual spaces. ACA reached a significant turning point in
1998 when White and McCain ( 1998 ) applied ACA to information science in their
thorough study of the field. Since then ACA has flourished and has been adopted
by researchers across a number of disciplines beyond the field of citation analysis
itself. Their paper won the best JASIS paper award. With both ACA and DCA at our
hands, we begin to find ourselves in a position to compare and contrast messages
conveyed through different co-citation networks of the same topic as if we were
having two pairs of glasses.
Typically, the first step is to identify the scope and the focus of ACA. The raw
data are either analyzed directly or, more commonly, converted into a correlation
matrix of co-citation. Presentations often combine MDS with cluster analysis or
PCA. Groupings are often produced by hierarchical cluster analysis. Figure 5.10
illustrates a generic procedure of a standard co-citation procedure. For example,
node placement can be done with MDS; clustering can be done with the single-
or complete-link clustering; PCA might replace clustering. In practice, some
researchers choose to work on raw co-citation data directly, whereas others prefer