Date: Sun 26 Sep 2004 - 09:22:12 CEST
> In the figures,
> every number corresponds to an existing subdiscipline formed
> by a basic science working outside its "preferred" level
> e.g., 1: chemical physics, 2: biophysics, 5:
> biochemistry, 8: psychobiology, 10: psychosociology, etc.
> (see figures and complete text).
Dear Pedro and colleagues,
These questions about the relations between disciplines and specialities can
be studied empirically by using the aggregated citations among journals. At
the aggregated level the incidental citations among fields become
insignificant and the pattern of citations comes to the fore. I have worked
on these matrices intensively since 1986. A recent paper is:
Clusters and Maps of <http://www.leydesdorff.net/jcr01/art/index.htm>
Science Journals Based on Bi-connected Graphs in the Journal Citation
Reports, Journal of Documentation, 60(4), 2004, 371-427. [The classification
and mapping of journals in the Science Citation Index 2001 is available at
http://www.leydesdorff.net/jcr01.] <pdf-version
<http://www.leydesdorff.net/jcr01/jdoc04.pdf> >
As an example, I feeded the citation pattern 2003 of the journal Biosystems
into the system
.
Rotated Component Matrix(a)
Component
1
2
3
4
5
6
7
8
9
TRENDS GENET
.948
.175
.107
BIOESSAYS
.925
.170
.141
.138
.150
CELL
.867
.165
.122
.187
P NATL ACAD SCI USA
.845
.233
.147
.329
.141
BIOCHEM BIOPH RES CO
.802
.142
.351
.113
J MOL EVOL
.762
.171
.128
.110
.309
-.221
NATURE
.723
.257
.305
.228
.120
.148
.296
SCIENCE
.722
.257
.302
.196
.121
.143
.270
GENETICS
.694
-.124
.148
-.103
-.147
-.121
-.209
-.390
ANN NY ACAD SCI
.674
.627
.179
.115
NUCLEIC ACIDS RES
.622
.368
.506
-.206
BIOSYSTEMS
.590
.149
.272
.145
.379
.277
J NEUROPHYSIOL
.910
J NEUROSCI
.295
.866
BIOL CYBERN
.826
NEURON
.466
.735
.125
J PHYSIOL-LONDON
.719
AM NAT
.864
.224
EVOLUTION
.118
-.117
.843
-.228
P ROY SOC LOND B BIO
.341
.829
.206
.118
TRENDS ECOL EVOL
.431
.813
.147
.123
PHYS REV E
.914
PHYS REV LETT
.875
PHYSICA D
.875
CHAOS SOLITON FRACT
.783
BIOCHEMISTRY-US
.234
.872
BIOPHYS J
.201
.100
.806
J MOL BIOL
.443
.753
.240
B MATH BIOL
.222
.188
.904
.191
J MATH BIOL
-.102
.108
.848
-.151
-.115
J THEOR BIOL
.437
.299
.158
.718
.188
EVOL COMPUT
.956
IEEE T EVOLUT COMPUT
.941
INT J SYST EVOL MICR
-.143
.740
BIOINFORMATICS
.523
.220
.131
.615
-.230
ARTIF LIFE
.266
-.102
.132
.691
Extraction Method: Principal Component Analysis. Rotation Method: Varimax
with Kaiser Normalization.
a Rotation converged in 9 iterations.
This is based on the citing patterns. The factor matrix clearly shows the
interdisciplinary position of the journal in the relevant citation
environments..
Similarly, one can generate a picture of the cited patterns of each journal.
With kind regards,
Loet
_____
Loet Leydesdorff
Amsterdam School of Communications Research (ASCoR)
Kloveniersburgwal 48, 1012 CX Amsterdam
Tel.: +31-20- 525 6598; fax: +31-20- 525 3681
<mailto:loet@leydesdorff.net> loet@leydesdorff.net ;
<http://www.leydesdorff.net/> http://www.leydesdorff.net/
<http://www.upublish.com/books/leydesdorff-sci.htm> The Challenge of
Scientometrics ; <http://www.upublish.com/books/leydesdorff.htm> The
Self-Organization of the Knowledge-Based Society
