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Fig. 5.19 A Pathfinder
network showing an author
co-citation structure of 367
authors in hypertext research
(1989-1998). The color of a
node indicates its specialty
membership identified by
PCA: red for the most
predominant specialty, green
the second, and blue the third
(© 1999 IEEE)
which corresponded to 39 specialties in the field of hypertext. Authors were colored
by factor loadings of the top three largest specialties. The strongest specialty was
colored in red. The next two strongest ones were in green and blue, respectively.
The strongest specialty branches out from the top of the ring structure, whereas the
second strongest specialty appears to concentrate around the lower left-hand corner
of the ring.
The colored PCA overlay allows us to compare structural positions of authors
and their presence in the three major specialties. Partitioning the network by
color provides a unique and informative alternative to traditional non-overlapping
partitions based on clustering and other mutually exclusive partition schemes. Less
restricted partition schemes are most appropriate when we deal with invisible
colleges - identifying the membership of a scientist is rarely a clear cut. After all,
giants in scientific frontiers may well appear simultaneously in several specialties.
Figure 5.20 shows a landscape view of the same author co-citation network
enhanced by corresponding citation history of each author. Most cited authors
became landmarks in the scene. The shape of the invisible college associated with
this field of study began to emerge.
We explored two types of animations: animations that display the distributions of
specialties and animations that display the growth of citation bars in the landscape.
We chose to keep the underlying co-citation network constant, which serves as a
base map, and let the citation profiles grow. In effect, we have a growing thematic
overlay within a static reference framework.
Applying Pathfinder network scaling to co-citation networks not only enriched
the applications of Pathfinder networks, but also let to deeper insights into the
nature of Pathfinder network scaling and how to interpret various patterns emerged
from such representations. Now we can systematically explain the meaning of a
co-citation network. For example, documents or authors in the centre or a relatively
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