Paper on scientometrics
loet at LEYDESDORFF.NET
Sun Jul 28 13:15:38 EDT 2013
Dear David and colleagues,
One basic problem is that we do not have an agreed upon operational
definition of revolution. So if we are measuring different things under the
same name we may get differing results that do not actually disagree.
Although we don't have such a definition, it is not so difficult to point ex
post to instances that have provided breakthroughs and led to the
development of new specialties. For example, "oncogene" in 1988,
"interference RNA" in 1998; super-conductivity in 1987(?) at higher
It seems to me that there are two main questions that should not be
1. is it possible to predict such breakthroughs in terms of a specific set
of conditions? The notion of a void (as Chaomei named it) seems relevant
here: structural holes; synergies among redundant research programs, etc.
2. ex post: early warning indicators, upscaling conditions, etc. For
example, in the case of RNA-interference we hypothesized that first
preferential attachment is with the initial inventors, but then the system
globalizes and on preferentially attaches with world centers of excellence
(in Boston, London or Seoul). (Leydesdorff & Rafols, 2011).
In my opinion, the problem is that one can study these cases, derive
hypotheses, but then during the upscaling one fails to develop predictors
from them. For example, we found an entropy measure for new developments in
(Leydesdorff et al., 1994), but it did not work for the prediction at the
level of the file of aggregated journal-journal citations. Ron Kostoff's
tomography was another idea that eventually did not lead us to the
prediction of emerging fields (Leydesdorff, 2002).
I mean to say that if one finds for example, that an important new
development leads to a new citation structure, is it then also possible to
scan the database for such structures and in order to find new developments?
. Loet Leydesdorff, Susan E. Cozzens, and Peter Van den Besselaar,
Tracking Areas of Strategic Importance using Scientometric Journal Mappings,
Research Policy 23 (1994) 217-229.
. Loet Leydesdorff, Indicators of Structural Change in the Dynamics
of Science: Entropy Statistics of the
<http://www.leydesdorff.net/jcr/index.htm> SCI Journal Citation Reports,
Scientometrics 53(1) (2002) 131-159.
. Loet Leydesdorff & Ismael Rafols, How do emerging technologies
conquer the world? An exploration of patterns of diffusion and network
formation <http://www.leydesdorff.net/et/index.htm> , Journal of the
American Society for Information Science and Technology 62(5) (2011)
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