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generated by a method called
geometric triangulation,
which is different from the
MDS approach used in Small's earlier work and in similar studies in the US and
Europe (Garfield
1996
).
Henry Small and Belver Griffith initiated co-citation analysis for identifying and
mapping specialties from the structure of scientific literature (Small and Griffith
1974
). Articles A and B have a co-citation count of
k
if there are
k
articles and each
of them cites both articles A and B. The co-citation rate of A and B is defined as
the number of such instances. A high co-citation rate implies a strong intellectual
tie between two articles.
In a longitudinal study of collagen research, Henry Small tracked the movement
of specialties in collagen research using a cluster-based approach (Small
1977
).
He emphasized the fundamental role of systematic and consistent methodological
frameworks. He used the frequency of co-citation to measure the strength of the
association between articles on the topic. He marked clusters of highly cited articles
in MDS maps with contour lines so that he could track rapid sifts in research focus
from 1 year to another as articles moved in and out key cluster contours and used it
as an indicator of “revolutionary” changes.
In the 1980s, the Institute for Science Information (ISI)
published the Atlas of
Science in Biochemistry and Molecular Biology
, which identified more than 100
distinct clusters of articles, known as research front specialties, and provided a
distinct snapshot of scientific networks. The Atlas was constructed based on co-
citation relationships between publications in the field over a period of 1 year. In
1989, Garfield and Small explained how software like SCI-Map could help users
navigate the scientific literature and visualize the changing frontiers of science based
on citation relationships (Garfield and Small
1989
). Henry Small described in detail
his citation mapping approach to visualizing science. Figure
5.6
shows a global map
of science for 1996 produced by co-citation mapping. The map highlighted major
connections among disciplines such as economics, neuroscience, biomedicine,
chemistry, and physics. The size of a circle was made proportional to the volume of a
particular scientific literature, for example, the large biomedical circle in the center
of the map indicating the huge number of biomedicine publications in journals.
Computer science, shown as a relatively small circle in the map, linked to imaging
and economics. The small volume of computer science reflected the fact that journal
publications are merely a small proportion of the entire computer science literatures,
typically including conference proceedings, technical reports, and preprints. One
can also zoom into the global map of science and examine local structures (See
Figs.
5.7
and
5.8
).
MDS maps and clustering algorithms are typically used in co-citation analysis
to represent co-citation structures. There is an increasing interest in using graph-
drawing techniques to depict the results of co-citation analysis, including minimum
spanning trees (MST) and Pathfinder networks (PF). The increased use of the
metaphor of an information landscape is another trend, in which the entire structure
can be rendered as a mountain terrain or a relief map.
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