Transcript Slide 1

Tejashwini B.
UGC-Junior Research Fellow
DOS in Library & Information Science
University of Mysore
Mysore-06
SCIENTOMETRICS DEFINITION
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It is the quantitative study of science output or outcome
in any form, not just records or bibliographies. It
comprises all the metrics studies related to science
indicators, citation analyses, research evaluation, etc.
 Scientometrics is the science of measuring and
analysing science. In practice, scientometrics is often
done using bibliometrics which is a measurement of the
impact of (scientific) publications.

HISTORY OF SCIENTOMETRICS
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Derek De Solla Price(1922-1983)
In his book entitled “Little Science –
Big Science” (1963), Price analyzed
the recent system of science communication
and thus presented the first systematic
approach to the structure
of modern science applied to
the science as a whole.
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1969, Vassily V. Nalimov & Z. M. Mulchenko
coined the Russian equivalent of the term
‘scientometrics’ (‘naukometriya’).
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 In
EUGENE GARFIELD (1925-)
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The founder and chairman
of the Institute for Scientific
Information (now part of Thomson
Reuters). In the early 1955 he
developed the Science Citation Index,
the world’s first large
multidisciplinary
citation database.
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The journal Impact Factor was first used as a measure
for comparing journals independently of “size” and to
help select journals for the Science Citation Index
(SCI).
 Garfield later recognized the power of the IF for
journal evaluation and considered it also a journal
performance indicator.

ROBERT K. MERTON (1910-2003)
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Robert K. Merton represents the
sociologists’ view of scientometrics.
Among his most famous
ideas related to science and
its measurement,
the Mathew effect and
his notion of citation as a
reward system (currency of science)
should be mentioned.
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REASONS FOR QUANTITATIVE STUDIES OF
LITERATURE
Analysis of structure and dynamics

Understanding of patterns
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
search for regularities - predictions possible
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verification of models, assumptions
Rationale for policies & design
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Qualitative methods often depend on assertions.
‘authoritative’ statements, anecdotal evidence
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Success of statistical methods in social sciences

Need for justification & basis for decisions

Something can be counted - irresistible
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Science searches for regularities
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WHAT STUDIED?
author(s)
 origin
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Governed by data available in documents or
information resources in general - that what can
be counted
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
organization, country, language
source

journal, publisher, patent …
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VARIABLE: AUTHORS
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number in a subject, field, institution, country
growth
correlation with indicators like GNP, energy etc.
productivity e.g. Lotka’s law
collaboration - co-authorship, associated networks
dynamics - productive life, transcience, epidemics
papers/author in a subject
mapping
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VARIABLE: ORIGIN
Rates of production, size, growth by
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country, institution, language, subject
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Comparison between these
 Correlation with economic & other indicators
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VARIABLE: SOURCES
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Scatter - quantity/yield distribution
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information explosion - exponential laws
 time movements, life cycles
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Concentration most often on journals
 Growth, dynamics, numbers
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Bradford’s law
Various distributions
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by subject, language, country
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VARIABLE: CONTENTS
Analysis of texts
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distribution of words – Zipf’s law
 words, phrases in various parts
 subject analysis, classification
 co-word analysis
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VARIABLE: REPRESENTATION
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frequency of use of index terms, classes
 distribution laws - key terms where?
 thesaurus structure
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VARIABLE: CITATIONS
Studied a lot; many pragmatic results
base for citation indexes, web of science, impact factors, cocitation studies etc
Derived:
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number of references in articles
 number of citations to articles
 bibliographic coupling
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CITATIONS
co-citations
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centrality
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of authors, papers
validation with qualitative methods
 impact
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author connections, subject structure, networks, maps
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… MORE
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VARIABLE: UTILIZATION
frequency
 distribution of requests for sources, titles
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e.g. 20/80 law
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relevance judgment distributions
 circulation patterns
 use patterns
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LAWS
& METHODS
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Lotka’s law
 Bradford’s law
 Zipf’s law
 Impact factor
 H –index(g, A, p etc.)
 Citation structures
 Citation Analysis
 Co-citation structures
 Co-word Analysis
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ISSUES IN SCIENTOMETRCS
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‘In databases we trust’
 ‘In names we trust’
 Citation networks
 Linguistic networks
 Mobility networks
 Online networks
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Number of Citations
Number of Citations
30
25
20
15
15
10
5
10
5
2002
0
2003
2004
2005
2006
2007
2008
2009
2010
2011
Year of Citation
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Year of Citation
Figure 2e: Year-wise growth of citations in Theoretical Research
Figure 2f: Year-wise growth of citations in Detectors and
Nuclear Instrumentation
3.0
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2.0
Number of Citations
Number of Citations
2.5
1.5
1.0
0.5
10
5
0
0.0
2002
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2003
2004
2005
2006
2007
2008
2009
2010
Year of Citation
Figure 2g: Year-wise growth of citations in Accelerators and
Instrumentation
2011
2002
2003
2004
2005
2006
2007
2008
2009
2010
Year of Citation
Figure 2h: Year-wise growth of citations in Interdisciplinary
Research and Applications
2011
300000
India is at 7th position
250000
200000
C ountries
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United-States
Japan
Germany
United-Kingdom
France
USSR
India
Russian Federation
Italy
China
Canada
Brazil
Switzerland
Poland
Netherlands
Australia
Sweden
Czechoslovakia
Austria
Mexico
350000
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Number of publications
Nuclear S & T : A Global Perspective
(INIS 1970-2002)
400000
150000
100000
50000
0
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RANKING OF UNIVERSITIES
Total Score
1
Harvard University
597.67
2
University Of Toronto
572.40
3
Johns Hopkins University
572.14
4
University Of California Berkeley
571.83
5
Stanford University
571.78
6
University of Oxford
571.17
7
University of California Los Angeles
566.66
8
University of Washington Seattle
564.72
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Massachusetts Institute of Technology
563.38
10
University of Michigan Ann Arbor
563.23
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University
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Rank
23
Country
POLAND
INDIA
SPAIN
CANADA
RUSSIA
ITALY
ENGLAND
PEOPLES-R-CHINA
FRANCE
GERMANY
6000
4000
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JAPAN
8000
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USA
Number of publications
12000
Global View of Research
in Raman Spectroscopy
10000
2000
0
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