The journal Impact Factor (IF) is not comparable among fields of Science and Social Science .... Indexes such as the JCR subject category list accommodate.
Comparing journals from different fields of Science and Social Science through a JCR Subject Categories Normalized Impact Factor
P. Dorta-González a*, M.I. Dorta-González b a
Departamento de Métodos Cuantitativos en Economía y Gestión, Universidad de Las Palmas de Gran
Canaria, Gran Canaria, España;
b
Departamento de Estadística, Investigación Operativa y Computación,
Universidad de La Laguna, Tenerife, España.
ABSTRACT The journal Impact Factor (IF) is not comparable among fields of Science and Social Science because of systematic differences in publication and citation behaviour across disciplines. In this work, a decomposing of the field aggregate impact factor into five normally distributed variables is presented. Considering these factors, a Principal Component Analysis is employed to find the sources of the variance in the JCR subject categories of Science and Social Science. Although publication and citation behaviour differs largely across disciplines, principal components explain more than 78% of the total variance and the average number of references per paper is not the primary factor explaining the variance in impact factors across categories. The Categories Normalized Impact Factor (CNIF) based on the JCR subject category list is proposed and compared with the IF. This normalization is achieved by considering all the indexing categories of each journal. An empirical application, with one hundred journals in two or more subject categories of economics and business, shows that the gap between rankings is reduced around 32% in the journals analyzed. This gap is obtained as the maximum distance among the ranking percentiles from all categories where each journal is included.
Keywords: citation, impact factor, journal evaluation, source normalized indicator, JCR subject categories.
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1. Introduction The Impact Factor (IF) published in the Journal Citation Reports (JCR) by Thomson Reuters is defined as the average number of citations to each journal in a current year to ‘citable items’ published in that journal during the two preceding years. Since its formulation (Garfield, 1972), the IF has been criticized for some arbitrary decisions involved in its construction. The definition of ‘citable items’ (articles, notes, and reviews), the focus on two preceding years as representation of impact at the research front, etc., have been discussed in the literature (Bensman, 2007) and many possible modifications and improvements have been suggested (Althouse et al., 2009). In response, Thomson Reuters has added the Five-year Impact Factor, the Eigenfactor Score, and the Article Influence Score (Bergstrom, 2007) to the journals in the online version of the JCR, in 2007 (see Bornmann & Daniel, 2008, for a review in citation measures). While the extension of the IF to a five-year time window is direct, the other recent measures can be considered too complex (Waltman & Van Eck, 2010) and they do not solve the problem of comparing journals from different fields of science. The problem of field-specific differences in citation impact indicators comes from institutional research evaluation (Leydesdorff & Opthof, 2010a; Opthof & Leydesdorff, 2010; Van Raan et al., 2010). Citation distribution varies with fields of science and, in some cases, across specialties within fields (Dorta-González & Dorta-González, 2010, 2011a,b). However, institutes are populated by scholars with different disciplinary backgrounds and research institutes often have among their missions the objective of integrating interdisciplinary bodies of knowledge (Leydesdorff & Rafols, 2011; Wagner et al., 2011). There are statistical patterns which are field-specific and allow the normalization of the IF. Garfield (1979a,b), proposes the term ‘citation potential’ for systematic differences among fields of science based on the average number of references per paper. For example, in the biomedical fields long reference lists with more than fifty items are common, but in mathematics short lists with fewer than twenty references are the standard. These differences are a consequence of the citation cultures, and can be expected to lead to significant differences in the IF across fields of science because the probability of being cited is affected. The fractionally counted IF corrects these differences in terms of the sources of the citations (Leydesdorff & Bornmann, 2011; Moed, 2010; Zitt & Small, 2008). Using fractional counting, a citation in a citing paper containing n references counts 1/n, instead of 1, as is the case with integer counting. In relation to the source-normalization, Zitt & Small (2008) propose the Audience Factor (AF) using the mean of the fractionally counted citations to a journal. This mean is then divided by the mean of all journals included in the Science Citation Index. Similarly, Moed (2010) divides a 2
modified IF (with a window of three years and a different definition of citable items) by the median number of references in the Scopus database. He proposes the resulting ratio as the Source Normalized Impact per Paper (SNIP) which is now in use as an alternative to the IF in the Scopus database (Leydesdorff & Opthof, 2010b). The Scimago Journal Ranking (SJR) considers the prestige of the citing journals (González-Pereira et al., 2011), and even though this is useful for the ranking of journals, the value of the indicator is difficult to interpret (Waltman et al., 2011). Another important source of variance between fields is related to the dissemination channel of the research activity results. For example, researchers in social sciences and humanities publish more in books than in journals, and researchers in computer science publish their results more in conference proceedings than in journal articles (Chen & Konstan, 2010; Freyne et al., 2010). Differences between fields citations are caused mainly by the different ratio of references to journals included in the JCR as opposed to references to ‘non-source items’ (e.g., books), whereas differences in the lengths of reference lists are mainly responsible for inflation in the IF (Althouse et al., 2009). Most efforts to classify journals in terms of fields of science have focused on correlations between citation patterns in core groups assumed to represent scientific specialties (Leydesdorff, 2006; Rosvall & Bergstrom, 2008 and 2010). Indexes such as the JCR subject category list accommodate a multitude of perspectives by listing journals under different groups (Pudovkin & Garfield, 2002; Rafols & Leydesdorff, 2009). In this sense, Egghe & Rousseau (2002) define the Relative Impact Factor (RIF) in a similar way as the IF, taking all journals in a category as a meta-journal. This indicator in the JCR is called Aggregate Impact Factor (AIF). Furthermore, normalizations based on the journal ranking in the category (Sombatsompop & Markpin, 2005), and the maximum value of the IF jointly with the median in the category (Ramírez et al., 2000) have been proposed. However the positions of individual journals on the merging specialties remain difficult to determine with precision and some journals are assigned to more than one category. This is the case of Science, Nature, and the Proceedings of the National Academy of Science of the USA (PNAS), which are examples of high prestige multidisciplinary journals. Many others journals cover two or more specialties. Therefore, journals cannot easily be compared, and classification systems based on citation patterns hence tend to fail. When a journal publishes work from several subject categories, its performance may be better when seen from the standpoint of one subject category than from the other (multidisciplinary effect). The categories in the JCR were created in order to compare journals within the same category. However, what is to be done when a journal is included in more than one category? In this work, a normalization process considering all journals in the indexing categories is proposed. In order to
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compare the normalized impact indicator with the IF, an empirical application, with one hundred journals in two or more subject categories of economics and business, is presented. In addition to the average number of references and the ratio of references to journals included in the JCR, there exist some other sources of variance between fields. In this work also we decompose the aggregated impact factor into five main sources of variance and calculate them in all the categories of the JCR. Out of the five main sources there are three new factors: the field growth, the ratio of JCR references to the target window, and the proportion cited to citing items.
2. Decomposing the Aggregate Impact Factor of a field into its main components 2.1 Impact Factor of a journal A journal impact indicator is a measure of the number of times that articles published in a census period cite articles published during an earlier target window. The IF reported by Thomson Reuters has a one year census period and uses the two previous years as the target window. As an average, the IF calculation is based on two elements: the numerator, which is the number of citations in the current year to any items published in a journal in the previous two years, and the denominator, which is the number of ‘citable items’ published in the same two years (Garfield, 1972). Journal items include ‘citable items’ (articles, notes, and reviews), but also letters, corrections and retractions, editorials, news, and other items. Let Ati be the number of citable items in journal i in year t. Let NCited ti be the number of times in year t that the year t-1 and t-2 volumes of journal i are cited by journals in the JCR. Then, the Impact Factor of journal i in year t is
NCited ti IFt i . At 1 Ati2 i
(1)
2.2 Aggregate Impact Factor (AIF) of a field Let F be the set of all journals in a specific field, where the fields are equivalent to the JCR subject
categories. Denoting AtF iF Ati and NCited tF iF NCited ti , the Aggregate Impact Factor (AIF) is the ratio between the citations in year t to citable items in any journal of field F in years t-1 and t-2, and the number of citable items published in years t-1 and t-2, that is,
AIFt
F
iF
iF
NCited ti
Ati1 Ati2
4
NCited tF . AtF1 AtF2
(2)
The AIF can also be expressed as a weighted mean impact factor. Consider a formulation that assigns weights proportional to the number of citable items in the target years. The weight for journal i in year t is
fti Notice that
iF
AIFt
F
Ati1 Ati2 . AtF1 AtF2
(3)
f t i 1 . Then, from equations (1), (2), and (3),
iF F t 1
NCited ti
A AtF2
NCited ti Ati1 Ati2 i IFt f t i IFt i . F F F F iF At 1 At 2 iF At 1 At 2 iF
(4)
2.3 Components in the Aggregate Impact Factor of a field It is possible to decompose the AIF into five main variables. We will show in section 4 that these variables are normally distributed and different across fields. The variable atF is a measure of the field growth while the others ( rt F , ptF ,wtF ,btF ) are related with the citation habits in the field.
-
Field growth rate
A field can grow for two reasons; by incorporating new journals into the field or by publishing more
items
in
some
indexed
journals.
However,
a
field
can
also
decrease.
Let
atF AtF / ( AtF1 AtF2 ) be the ratio of citable items in year t with respect to those appearing in the target window. This is a measure of the field growth. Note that atF 0.5 when AtF AtF1 AtF2 . If
atF 0.5 then the field is growing in the number of citable items. Conversely, if atF 0.5 then the field is reducing. For example, if a field is growing annually around 5%, then AtF 1.05 AtF1 , AtF1 1.05 AtF2 , and
atF ( 1.05 2 AtF2 ) / ( 2.05 AtF2 ) 1.05 2 / 2.05 0.538 . Some others ratios are atF 0.576 (10%) and atF 0.654 (20%). On the other hand, if a field is reducing annually around 5%, then
AtF 0.95 AtF1 , AtF1 0.95 AtF2 , and atF ( 0.95 2 AtF2 ) / ( 1.95 AtF2 ) 0.95 2 / 1.95 0.463 . -
Average number of references
Let RtF be the total number of references in journals of field F in year t. Then rt F RtF / AtF is the average number of references in citable items of field F in year t. -
Ratio of references to JCR items
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Let J tF be the total number of references (in items of field F in year t) to journals in the JCR. This excludes unpublished working papers, conference proceedings, books, and journals not indexed by the JCR. Then ptF J tF / RtF is the ratio of number of references to number of JCR items. For example, if ptF 0.5 then half of the references are JCR items.
-
Ratio of JCR references to the target window
Let NCitingtF be the total JCR references in field F in year t within the target window. Then,
wtF NCiting tF / J tF is the ratio of JCR references in year t within the target window. For example, if wtF 0.25 then a quarter of the JCR references belong to the target window.
-
Proportion of cited to citing items in the target window
If i F , most of the citations to journal i came from journals within field F but some of them came from journals outside field F. Let btF NCited tF / NCitingtF be the proportion of cited to citing items in the target window. If btF 1 then citations received in field F are more than citations produced in field F (within the target window). Conversely, if btF 1 then citations received are less than citations produced. Therefore, the index btF is a measure of the field’s citations exchange. For example, if btF 1.1 then field F receives in the target window around 10% more citations than it produces.
2.4 Decomposing the AIF of a field into components The Aggregate Impact Factor of field F can be decomposed or factorized in the following way:
AIFt F atF rt F ptF wtF btF . (5) The proof is direct, considering that NCited tF can be expressed as: RtF J tF NCitingtF NCited tF NCited A F F AtF rt F ptF wtF btF . F F At Rt Jt NCitingt F t
F t
Therefore, from (2) and (6),
AIFt F
AtF rt F ptF wtF btF atF rt F ptF wtF btF . F F At 1 At 2
3. Categories Normalized Impact Factor (CNIF) 6
(6)
This is a field-normalized citation impact score, where the fields are equivalent to the JCR subject categories. We compare ‘actual’ citation counts to ‘expected’ counts based on the average impact score of all JCR-indexed journals assigned to a field. Let Ft1 ,Ft 2 ,...,Ft n be the subject categories where journal i is indexed in year t. Denoting by
Ft j Ft1 Ft 2 Ft n , then
AIFt
Ft j
i Ft j
iJCR
i Ft
NCited ti
Ati1 Ati2
j
.
In a similar way,
AIFt
JCR
iJCR
NCited ti
Ati1 Ati2
.
Let AIFt JCR / AIFt Ft be the normalized score of the meta-category Ft j . If AIFt JCR AIFt Ft then j
j
the score is one. Scores larger than one represent aggregate impact factors in the field below the average in the JCR, while scores lower than one represent aggregate impact factors in the field above the average in the JCR. We define the Categories Normalized Impact Factor of journal i in year t as:
CNIFt i
AIFt JCR AIFt
Ft j
IFt i
j
Notice that if AIFt Ft AIFt JCR , then the score is less than one and it reduces the impact factor of that journal. Conversely, if AIFt Ft AIFt JCR , then the score is higher than one and it increases the j
impact factor of that journal. In the particular case of a journal in only one category F,
CNIFt i
AIFt JCR IFt i F AIFt
The CNIF has an intuitive interpretation, similar to the IF. The CNIF is a measure of the number of times that articles published in year t cite, in a category-normalized proportion, articles published during the two previous years. Moreover, it is easy to calculate and allows for the comparison between fields.
4. Empirical application 7
4.1 Materials and Methods The underlying bibliometric data in the empirical application was obtained from the online version of the Journal Citation Reports (JCR) during the first week of October 2011. The JCR database (reported by Thomson Reuters – ISI, Philadelphia, USA) is available at the website www.webofknowledge.com. The IF reported by Thomson Reuters has a one year census period and uses the two previous years as the target window. In the JCR, journals are assigned by Thomson Reuters experts into one or more journal categories, according to cited and citing relationships with the journals in the categories (Pudovkin & Garfield, 2002). The journal categories, also referred to subject category list, are treated as fields and subfields of science. The 2010 Science edition contains 8073 journals classified into 174 subject categories. The 2010 Social Science edition contains 2731 journals classified into 56 subject categories. Given that these journal categories are well known, there is no reason to question the feasibility of using them in the field-normalization. Although most journals in the JCR are included in only one edition (Science or Social Science), there are some which are included in both. This happens, for example, with nine journals included in the category ‘Management’, in the Social Science edition, and in the category ‘Operations Research and Management Science’, in the Science edition. In the comparative analysis between the IF and the CNIF, and the estimation of the gap between rankings across categories, the five selected categories are: SS3 (BUSINESS), SS4 (BUSINESS, FINANCE), SS9 (ECON), SS29 (MANAGE), and S124 (OPER RES & MANAGE SCI). These five categories contain a total of 590 different journals. There are 490 journals in just one category, 98 journals in two categories, and 2 journals in three categories. Therefore, the number of journals in more than one category is exactly 100 (48 journals in SS3, 36 journals in SS4, 54 journals in SS9, 55 journals in SS29, and 9 journals in S124).
4.2 Results -
The Aggregate Impact Factor of the JCR subject categories
Table 1 shows the AIF for both editions of the JCR (i.e. Science and Social Science). At the bottom of Table 1 the aggregate index, the average, and the standard deviation for both editions, are also shown. Unlike the aggregate impact factor, that considers the size of the categories, in the average impact factor all the categories have the same weight. The AIF in Science is 2.920, around 58% higher than in Social Science which is 1.848. [Table 1 about here]
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There exists a great variance in the AIF within each edition. In Science, the categories with highest values are MULTIDISCIP SCI (9.707), CELL BIOL (6.453), and HEMATOL (5.310), whereas the lowest factors are for ENGN, MARINE (0.207), ENGN, PETROLEUM (0.565), and ENGN, AEROSPACE (0.628). In Social Science, the categories with the highest AIF are PSYCHIATRY (3.215), PSYCHOL, BIOL (2.682), and PSYCHOL, EXPT (2.590), whereas the lowest factors are for HIST (0.479), HIST OF SOCIAL SCI (0.623), and AREA STUDIES (0.640). Notice in Figure 1 that the AIF in Science is higher than in Social Science. [Figure 1 about here]
-
The components of the JCR subject categories
Table 1 shows also the components. There are important differences between categories, especially between categories from different editions. The average growth of the JCR is 0.57 (the JCR database annual growth is around 9%). This average growth is about 0.55 (7%) in the Science edition and around 0.62 (16%) in the Social Science edition. Therefore, the Social Science edition is growing over twice as much as the Science edition. This is due to the incorporation of journals in some categories of the Social Science edition in the last few years. This has occurred in categories HOSPITAL, LEIS, SPORT & TOUR (0.97), ETHNIC STUDIES (0.81), and HIST (0.78), for example. In Science, a great variance is observed. Note the case of BIOL (0.85) in comparison to ENGN, INDUSTRIAL (0.41), for example. The average number of references in Science is 37.18 while in Social Science it is 48.28. Therefore, a journal from a category of Social Science has on average 30% more references than a journal from a Science category. However, there exists a great variance within editions. Notice categories CELL & TISSUE ENGN (75.66), PALEONTOL (67.05), and HIST (66.28), in comparison to ENGN, MARINE (13.94), NUCLEAR SCI & TECH (19.21), and MATH (20.49), for example. The average ratio of references to JCR items is 0.75. In Science this average is 0.80 whereas in Social Science it is 0.60. Therefore, a journal from a Social Science category has on average 20% more references to non-JCR items than a journal from a Science category. However, there exists a great variance within editions. In Science, notice categories PHYS, ATOM, MOLEC & CHEM (0.94), CELL BIOL (0.93), and CHEM, ORGANIC (0.93), in comparison to ENGN, MARINE (0.39), HIST & PHILOS OF SCI (0.44), and COMP SCI, SOFT ENGN (0.56), for example. In Social Science, note categories PSYCHOL, BIOL (0.87), PSYCHOL, EXPT (0.83), and PSYCHIATRY (0.80), in relation to HIST (0.30), and CULTURAL STUDIES (0.32), for example. The average ratio of JCR references to the target window is 0.18. Therefore, one of each five JCR references is on average within the target window. There are few differences between editions (0.18 in Science and 0.20 in Social Science) but there exists a great variance within editions. The highest 9
ratios are 0.45 in AREA STUDIES, 0.35 in INT RELAT, and 0.33 in ENGN, MARINE. The lowest ratios are 0.10 in PALEONTOL, and 0.11 in GEOL and MANAGE. Finally, there exists a great variance in the proportion of cited to citing items. In Science, notice categories MULTIDISCIP SCI with 2.55, PHYS, MULTIDISCIP with 1.20, and HEMATOL with 1.18, in comparison to ENGN, MARINE with 0.28, HIST & PHILOS OF SCI with 0.30, and NURS with 0.41, for example. In Social Science, note category PSYCHOL, MATH with 1.16, in relation to HIST with 0.10, for example.
-
Cluster Analysis of the JCR categories
Table 2 shows a Cluster Analysis of the JCR categories according to the AIF components. Ward's method is the criterion applied in the hierarchical cluster analysis. We consider two levels of aggregation. The first cluster level (L1) is configured by closest categories in the publication and citation habits. The second level (L2) contains meta-clusters of categories that are relatively closer in the publication and citation habits. Although some clusters exclusively contain categories from the same edition (C4 and C8), in most cases there are categories from both editions of the JCR. There are two very large clusters (C5 and C6), with more than 25% of categories each. Note that around 70% of categories are clustered in C12 while about 4% of categories are not clustered. The non clustered group includes some popular categories such as S17 (BIOL), S113 (MULTIDISCIP SCI), and SS20 (HIST). [Table 2 about here]
-
Principal Component Analysis of the AIF
Table 3 shows the correlation between the main variables. Note that increasing the average number of references in a field rt F also increases the citations received NCited tF ; correlations of 0.95 and 0.89 in Science and Social Science, respectively. Something similar occurs with the number of references to JCR items J tF . Moreover, if a field produces more citations NCitingtF , then it also receives more citations NCited tF ; correlations of 0.98 and 0.87 in Science and Social Science, respectively. [Table 3 about here] The correlation between components in Table 3 is low or non-existent. There is a high correlation in Social Science between the ratio of references to JCR items J tF and the proportion of cited to citing
10
items btF . In this edition, categories citing more JCR items (closer to categories in Science) receive more citations from outside the category. In general, the components of the AIF correlate little or nothing with the AIF. This is shown in Figure 2. Whereas the correlation with the proportion cited to citing items is similar in both editions, the correlation with the ratio of references to JCR items is much higher in Social Science. The correlation with the average number of references is low in Science and there is no correlation in Social Science. [Figure 2 about here] Table 3 also shows the eigenvalues of a Principal Component Analysis (PCA). This eigenvalue decomposition of the correlation matrix in terms of component scores is used to find the causes of the variability in the dataset and sort them by importance. The principal components are guaranteed to be independent because the variables are normally distributed according to a KolmogorovSmirnov test (see also Table 4 and Figure 3). [Table 4 and Figure 3 about here] The analysis reveals that in Science the variance can be explained to a great degree by three major components: the ratio of references to JCR items ( J tF , 36.55%), the ratio of JCR references to the target window ( wtF , 20.93%), and the field growth ( atF , 20.60%). These components together explain 78.08% of the total variance. In Social Science, the variance can be explained to a great degree by only two major components: the ratio of JCR references to the target window ( wtF , 57.79%) and the proportion of cited to citing items in the target window ( btF , 23.50%). These components together explain 81.29 % of the total variance.
-
Comparing IF and CNIF
The CNIF is obtained for economics and business field journals in more than one JCR subject category (SS3, SS4, SS9, SS29, and S124). In each category, the percentile of a journal in the ranking is obtained as the position in the ranking divided by the number of journals in the category (x100%). A percentile is the value below which a certain percent of journals fall. The gap is defined as the maximum distance among the ranking percentiles from all categories where each journal is included. For instance, COMPUT ECON is in percentiles 67 and 85 for its two categories according to IF. The same procedure is applied to ranking percentiles obtained with CNIF. COMPUT ECON is
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ranked in percentiles 69 and 77 for its two categories according to CNIF. Then, the gap according to IF is 18 (85-67) and according to CNIF is 8 (77-69). There are important differences between the CNIF and the IF in most of the journals analyzed. The maximum gap in the IF case is 28 while in the CNIF case it is 17. The average gap in the IF case is 6.2 whereas the CNIF case is 4.2. Therefore, the maximum gap is reduced by around 39% and the average gap by about 32%. Moreover, in 51% of the journals analyzed the maximum gap has decreased. Finally, Figures 4 and 5 show the effect of the normalization on the Impact Factor. In all cases the impact of the journals analyzed has increased, some more than others (in a quantity higher than two in some cases). Therefore, the economics and business field is being penalized by the Impact Factor in comparison to the rest of fields in the JCR. [Figures 4 and 5 about here]
4.3 Discussion
The AIF in Science is around 58% higher than in Social Science. This is due to the fact that although on average there are over 30% more references in articles of Social Science, an important part of them are non-JCR items. In Social Science around 40% of the references are books and journals that are not indexed in the JCR, while in Science these are around 20% of the references. There exists a great variance in the AIF within each edition, in some cases between journals of relatively close categories. For example, the AIF of category MATH & COMP BIOL (3.038) is almost four times greater than category MATH (0.829). The categories with the highest AIF in Science are related to biomedicine. The lowest values are in engineering and mathematics. In Social Science, the categories with the highest values are related to psychology and some specialties of economics, such as health policy and management. The lowest factors are in categories related to history. The JCR database grows annually around 9%. The Social Science edition is growing over twice as much as the Science edition (16% and 7%, respectively). This is due to the incorporation of journals in some categories of the Social Science in the last few years. A journal from a category of Social Science has on average 30% more references and around 20% more references to non-JCR items than a journal from a Science category. The longest reference lists are produced in history and the shortest in engineering and mathematics. The highest proportions to non-JCR items are in physics, biology, and chemistry, whereas the lowest are in
12
engineering and computer science. In Social Science, the highest values are in psychology and the lowest in history. One of each five JCR references is on average in the target window. Curiously, some of the categories with the lowest proportion of references to JCR items have the highest proportion of citations in the target window. This is due to the fact that the older references correspond to books while the newer references correspond to articles. This happens, for example, in engineering and history. In some areas, such as mathematics, just one in eight JCR references is from the previous two years, in comparison to history where they are one in three. In general, the highest proportions cited to citing are in biomedicine and lowest are obtained in history and law. However, notice the exceptional case of category MULTIDISCIP SCI where more than half of the citations came from outside the category. In Social Science, categories citing more JCR items (closer to categories in Science) receive more citations from outside the category, some of them from Science categories. With respect to the Cluster Analysis of the JCR categories, C1 and C7 include, in general, those life sciences with an important social component, as well as those social sciences which use mathematical methods in a higher degree (health, psychology, economics, and business, for example). However, there exist important differences between C1 and C7, and they are not clustered jointly in the second level. Notice that S119 and SS30 (NURS) are in the same cluster (C1), as there are not enough differences between them to justify the existence of two similar categories in Science and Social Science editions. A similar case occurs with S79 and SS21 (HIST & PHILOS OF SCI) in cluster C2. Note that ECON is in C1, however BUSINESS and MANAGE are in C7; this highlights the heterogeneity of the economics and business field (observe also that BUSINESS, FINANCE is in C6). Clusters C2 and C4 contain those social sciences which use mathematical methods in a lower degree (education, sociology, linguistic, and law, for example). Finally, clusters C5 and C6 include formal, physical, technological, and life sciences (mathematics, physics, chemistry, engineering, and biomedicine, for example). The differences across categories within the same edition are in some cases greater than those which exist between some categories from different editions. This is the case of GERONTOL and PSYCHIATRY, close to Science, and S79 (HIST & PHILOS OF SCI), close to Social Science, for example. The variance in the AIF in Science can be explained to a great degree by three major components (the ratio of references to JCR items, the ratio of JCR references to the target window, and the field growth). In Social Science, the variance can be explained to a great degree by only two major 13
components (the ratio of JCR references to the target window and the proportion of cited to citing items in the target window). The principal components are different depending on the edition of the JCR. This is motivated because in Social Science there are many different disciplines in relation to the habits of publication and citation (economics and psychology versus history, for example). There are important differences between the CNIF and the IF for most of the journals analyzed. In the case of the CNIF, the maximum gap is reduced in more than half of the journals with respect to the IF. The average gap is also reduced by around a 32%.
5. Conclusions
The journal Impact Factor is not comparable among fields of science because of systematic differences in publication and citation behaviour across disciplines. A decomposing of the field aggregate impact factor into five normally distributed variables shows that, for the JCR subject categories of Science and Social Science, the variables that to a greater degree explain the variance
in the impact factor of a field do not include the average number of references. However, this is the factor that has most frequently been used in the literature to justify the differences between fields of science, as well as the most employed in the source-normalization (Leydesdorff & Bornmann, 2011; Moed, 2010; Zitt & Small, 2008). Therefore, it is necessary to consider some other sources of variance in the normalization process. In this sense, a normalized impact indicator based on the JCR subject category list is proposed and compared with the Impact Factor. This normalization is achieved by considering all the categories indexing each journal. An empirical application, with one hundred journals in two or more subject categories of economics and business, shows that the gap between rankings diminishes in one half of the cases analyzed and by around 32%. The field considered (economics and business) is an example of a heterogeneous area that is penalized by the Impact Factor, but not the only one, since the normalized impact has increased in all journals analyzed. Additionally, there are some other fields that are favored by the Impact Factor. This is the main reason why it is necessary to be cautious when comparing journal impact factors from different fields. In this sense, our index has behaved well in a big number of journals. Finally, we would emphasize the nature of JCR subject category data and the doubtfulness of obtaining results precise enough for the purpose no matter how sophisticated the mathematical and statistical technique.
Acknowledgements 14
This research has been supported by the Ministry of Science and Technology of Spain under the research project ECO2008-05589.
15
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18
Table 1: Aggregate Impact Factor components of the JCR subject categories in the 2010 Science and Social Science editions (S=Science, SS=Social Science, t=2010, - Data not available)
Code
JCR subject category (F)
S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30 S31 S32 S33 S34 S35 S36 S37 S38 S39 S40 S41 S42 S43 S44 S45 S46 S47 S48 S49 S50 S51 S52 S53 S54 S55 S56 S57 S58 S59 S60 S61 S62 S63 S64 S65 S66 S67 S68
ACOUSTICS AGR ECON & POLICY AGR ENGN AGR, DAIRY & ANIMAL SCI AGR, MULTIDISCIP AGRONOMY ALLERGY ANATOMY & MORPHOL ANDROL ANESTHESIOL ASTRON & ASTROPHYS AUTOM & CONTROL SYST BEHAV SCI BIOCHEM RES METHODS BIOCHEM & MOLEC BIOL BIODIVERS CONSERVAT BIOL BIOPHYS BIOTECH & APPL MICROBIOL CARDIAC & CARDIO SYST CELL & TISSUE ENGN CELL BIOL CHEM, ANALYT CHEM, APPL CHEM, INORG & NUCLEAR CHEM, MED CHEM, MULTIDISCIP CHEM, ORGANIC CHEM, PHYS CLIN NEUROL COMP SCI, ARTIF INTEL COMP SCI, CYBERNET COMP SCI, HARD & ARCHITEC COMP SCI, INFORMAT SYST COMP SCI, INTERDISCIP APPL COMP SCI, SOFT ENGN COMP SCI, THEORY & METHODS CONSTRUCT & BUILD TECH CRIT CARE MED CRYSTALLOGRAPHY DENTISTRY, ORAL SURG & MED DERMATOL DEV BIOL ECOL EDUC, SCI DISCIP ELECTROCHEM EMERGENCY MED ENDOCRIN & METABOL ENERGY & FUELS ENGN, AEROSPACE ENGN, BIOMED ENGN, CHEM ENGN, CIVIL ENGN, ELECT & ELECTRON ENGN, ENVIRONM ENGN, GEOLOG ENGN, INDUSTRIAL ENGN, MANUFACT ENGN, MARINE ENGN, MECHAN ENGN, MULTIDISCIP ENGN, OCEAN ENGN, PETROLEUM ENTOMOL ENVIRONM SCI EVOLUT BIOL FISHERIES FOOD SCI & TECH
References JCR JtF 87001 10771 65135 165027 140735 191377 82572 71567 14097 119952 587864 119510 277143 497392 2300858 123090 653552 467970 822862 554524 75741 1165303 548695 317360 497463 451855 1544644 765524 1643567 779590 187274 24119 54473 155262 227895 106893 97412 57189 153274 212892 218076 173103 211739 640059 48104 302448 68546 611906 336244 30755 276851 536301 199342 634985 259544 36820 74614 76839 2376 210921 132667 13260 24595 160936 863759 268481 150855 492829
Total RtF 110560 18343 82827 204241 193124 248439 94468 85796 16433 136540 753996 171369 312477 557611 2489594 159146 745525 514619 946753 604904 81945 1251961 628015 371130 538689 516337 1694928 824033 1770821 888013 285250 41678 95160 266542 322163 190047 164483 94782 170072 231353 252356 201837 229814 790606 72082 335975 82846 677374 437760 51921 328504 653171 295089 876499 327262 57045 105946 107999 6133 296658 199242 20338 36848 213373 1135683 315846 190662 604057
19
Citations to JCR items in the target window NCitedtF NCitingtF 11626 12872 1075 2395 13352 13182 15769 21064 15625 23783 19111 26277 16195 18216 6011 9494 1571 2069 20567 24750 131008 142737 17595 23622 32268 40224 98866 107235 428047 418919 13946 19505 74752 117221 76148 86868 137905 160035 115840 112024 18128 17421 268233 231292 100590 119856 49172 54563 58993 79483 57426 88072 324585 317737 111395 136404 285009 309709 132347 131593 29613 33535 2843 4387 8502 12437 23113 36675 30707 41310 14891 25990 14231 18296 7364 11475 29238 30200 32921 41283 26350 31184 26506 30138 36751 36553 84918 96279 5734 9403 56538 64829 8842 11669 113606 114554 65702 84990 3175 5620 42038 49317 76256 96697 30628 39031 112849 137704 52006 60964 3849 5303 11104 11265 11339 12720 214 776 25610 32354 14276 23749 1785 2306 1577 3498 14138 21061 133091 169848 40368 42326 12664 18730 58996 76620
AIF components atF 0.51 0.48 0.65 0.55 0.63 0.62 0.51 0.61 0.56 0.52 0.47 0.58 0.51 0.56 0.52 0.57 0.85 0.51 0.57 0.59 0.54 0.52 0.52 0.51 0.60 0.59 0.51 0.57 0.56 0.55 0.53 0.51 0.56 0.53 0.53 0.54 0.59 0.54 0.52 0.55 0.57 0.50 0.53 0.67 0.67 0.66 0.55 0.64 0.43 0.61 0.56 0.57 0.55 0.58 0.55 0.41 0.46 0.43 0.54 0.52 0.48 0.60 0.55 0.51 0.53 0.54 0.57
rtF 29.14 38.94 29.92 33.81 32.96 37.44 44.23 46.50 44.78 37.42 56.59 25.73 57.76 38.37 49.62 54.15 48.06 43.37 39.23 37.98 75.66 55.27 34.95 31.82 43.13 42.17 40.37 41.38 39.72 38.73 33.83 38.34 26.30 32.48 32.46 29.61 30.26 24.49 42.06 22.79 34.00 33.87 57.14 54.00 28.67 31.88 30.25 46.80 30.33 23.96 36.42 29.60 27.06 21.82 35.44 30.52 33.60 27.29 13.94 24.35 25.06 23.59 21.95 38.68 41.60 60.69 44.07 34.60
ptF 0.79 0.59 0.79 0.81 0.73 0.77 0.87 0.83 0.86 0.88 0.78 0.70 0.89 0.89 0.92 0.77 0.88 0.91 0.87 0.92 0.92 0.93 0.87 0.86 0.92 0.88 0.91 0.93 0.93 0.88 0.66 0.58 0.57 0.58 0.71 0.56 0.59 0.60 0.90 0.92 0.86 0.86 0.92 0.81 0.67 0.90 0.83 0.90 0.77 0.59 0.84 0.82 0.68 0.72 0.79 0.65 0.70 0.71 0.39 0.71 0.67 0.65 0.67 0.75 0.76 0.85 0.79 0.82
wtF 0.15 0.22 0.20 0.13 0.17 0.14 0.22 0.13 0.15 0.21 0.24 0.20 0.15 0.22 0.18 0.16 0.18 0.19 0.19 0.20 0.23 0.20 0.22 0.17 0.16 0.19 0.21 0.18 0.19 0.17 0.18 0.18 0.23 0.24 0.18 0.24 0.19 0.20 0.20 0.19 0.14 0.17 0.17 0.15 0.20 0.21 0.17 0.19 0.25 0.18 0.18 0.18 0.20 0.22 0.23 0.14 0.15 0.17 0.33 0.15 0.18 0.17 0.14 0.13 0.20 0.16 0.12 0.16
btF 0.90 0.45 1.01 0.75 0.66 0.73 0.89 0.63 0.76 0.83 0.92 0.74 0.80 0.92 1.02 0.71 0.64 0.88 0.86 1.03 1.04 1.16 0.84 0.90 0.74 0.65 1.02 0.82 0.92 1.01 0.88 0.65 0.68 0.63 0.74 0.57 0.78 0.64 0.97 0.80 0.84 0.88 1.01 0.88 0.61 0.87 0.76 0.99 0.77 0.56 0.85 0.79 0.78 0.82 0.85 0.73 0.99 0.89 0.28 0.79 0.60 0.77 0.45 0.67 0.78 0.95 0.68 0.77
Aggregate Impact Factor AIFtF 1.553 1.088 3.123 1.428 1.673 1.774 3.844 1.976 2.377 2.955 4.609 1.532 3.048 3.822 4.435 2.688 4.114 3.291 3.256 4.277 6.453 2.906 2.207 2.404 2.795 4.586 2.853 3.615 3.238 1.940 1.395 1.203 1.583 1.652 1.240 1.404 1.121 3.924 1.681 1.966 2.525 4.583 3.094 1.529 3.615 2.123 4.304 2.912 0.628 2.848 1.940 1.593 1.541 3.258 1.132 1.450 1.307 0.207 1.127 0.928 0.998 0.565 1.409 2.507 4.116 1.579 1.942
S69 S70 S71 S72 S73 S74 S75 S76 S77 S78 S79 S80 S81 S82 S83 S84 S85 S86 S87 S88 S89 S90 S91 S92 S93 S94 S95 S96 S97 S98 S99 S100 S101 S102 S103 S104 S105 S106 S107 S108 S109 S110 S111 S112 S113 S114 S115 S116 S117 S118 S119 S120 S121 S122 S123 S124 S125 S126 S127 S128 S129 S130 S131 S132 S133 S134 S135 S136 S137 S138 S139 S140 S141 S142 S143 S144 S145 S146 S147
FORESTRY GASTROEN & HEPATOL GENET & HERED GEOCHEM & GEOPHYS GEOGRAPHY, PHYS GEOL GEOSCI, MULTIDISCIP GERIATR & GERONTOL HEALTH CARE SCI & SERV HEMATOL HIST & PHILOS OF SCI HORTICULTURE IMAG SCI & PHOTO TECH IMMUNOL INFECTIOUS DIS INSTRUM & INSTRUMENTAT INTEGRAT & COMPL MED LIMNOL MARINE & FRESH BIOL MAT SCI, BIOMAT MAT SCI, CERAM MAT SCI, CHARAC & TEST MAT SCI, COAT & FILMS MAT SCI, COMPOSITES MAT SCI, MULTIDISCIP MAT SCI, PAPER & WOOD MAT SCI, TEXT MATH & COMP BIOL MATH MATH, APPL MATH, INTERDISCIP APPL MECHAN MED ETH MED INFORMAT MED LAB TECH MED, GEN & INTERNAL MED, LEGAL MED, RES & EXPT METALL & METALL ENGN METEOROL & ATMOS SCI MICROBIOL MICROSCOPY MINERAL MIN & MINERAL PROC MULTIDISCIP SCI MYCOL NANOSCI & NANOTECH NEUROIMAG NEUROSCI NUCLEAR SCI & TECH NURS NUTRIT & DIETET OBSTETR & GYNECOL OCEANOGRAPHY ONCOL OPER RES & MANAGE SCI OPHTHALMOL OPTICS ORNITHOL ORTHOPED OTORHIN PALEONTOL PARASITOL PATHOL PEDIATR PERIPH VASCULAR DIS PHARMACOL & PHARM PHYS, APPL PHYS, ATOM, MOLEC & CHEM PHYS, CONDEN MATTER PHYS, FLUIDS & PLASM PHYS, MATH PHYS, MULTIDISCIP PHYS, NUCLEAR PHYS, PARTIC & FIELDS PHYSIOL PLANT SCI POLYMER SCI PRIMARY HEALTH CARE
118549 382940 759905 324472 160804 93025 697181 138082 151209 436060 27945 83424 45101 826396 296452 205016 45667 73679 353748 161212 80794 25396 147205 52688 1534898 21449 23909 148002 304735 371885 154935 325669 12392 43039 84687 564352 31589 558834 256599 279224 656715 27154 78015 27955 379543 53821 661585 93439 1618720 113692 125366 286862 301783 192373 1061251 153260 241331 458808 38828 243535 107942 114685 158367 253772 359622 355361 1316587 945463 571932 783797 214211 261378 573143 161221 371309 460753 672802 507387 26602
163891 420138 849856 382922 210478 123641 873861 165247 216231 472192 62939 105471 61322 902431 340308 265740 61939 90960 439034 180555 94437 38432 162025 67083 1718357 31552 34522 178634 410885 497222 207574 416158 21839 63614 100724 707658 45286 632036 309126 336111 729125 33809 95651 40715 451475 66081 722178 101390 1768206 151346 191459 342612 350442 238310 1162357 212548 268410 516733 50439 274007 128555 155830 184377 288633 430521 387120 1505438 1053047 609551 842466 240795 309310 653806 183704 411286 508333 801562 564922 37017
20
10745 77128 156577 33619 14939 7929 76510 19901 21434 109358 1678 7471 5867 176305 67287 35387 5667 6712 33305 27166 10855 3345 22364 6749 287829 2098 3280 23779 30156 43713 19456 40233 1756 6730 11600 145040 4010 84168 33430 37740 119330 4693 7341 4039 206138 5867 145992 15479 245526 16609 10869 46423 44212 18538 248653 20324 34700 83455 2483 31353 12514 7777 23053 36577 49629 79062 184677 215235 69842 156603 29475 35684 133654 19947 67830 62539 84660 70658 3279
16473 75259 150409 42544 22751 10439 95789 26049 33354 92940 5515 11143 7468 172838 69288 45316 8647 15236 45527 28420 11926 4321 24633 7675 309530 3852 4267 28791 37579 55245 23504 46736 3911 9045 16603 123869 8185 111221 45099 46993 120871 4851 9567 4725 80965 8038 152401 15648 259773 21096 26587 49255 54848 24957 229993 21253 38015 95436 4803 32722 15689 11907 29583 47847 63818 70290 268016 203512 91796 151310 34286 41979 111266 26941 80556 69011 98536 85871 6877
0.54 0.52 0.53 0.54 0.55 0.51 0.53 0.56 0.62 0.51 0.59 0.58 0.60 0.51 0.54 0.54 0.68 0.59 0.50 0.63 0.45 0.54 0.51 0.58 0.55 0.56 0.55 0.61 0.55 0.60 0.52 0.56 0.56 0.56 0.55 0.61 0.59 0.61 0.52 0.55 0.55 0.48 0.51 0.46 0.58 0.58 0.60 0.57 0.53 0.49 0.66 0.54 0.56 0.53 0.55 0.52 0.52 0.56 0.51 0.57 0.60 0.56 0.58 0.57 0.55 0.56 0.54 0.52 0.50 0.53 0.57 0.49 0.49 0.52 0.53 0.51 0.56 0.55 -
45.07 40.17 49.95 49.78 59.09 57.08 48.47 46.67 35.22 44.98 48.08 34.99 37.78 45.73 36.20 23.50 38.74 46.86 49.14 39.30 24.40 19.84 27.61 26.58 32.07 24.59 23.01 37.38 20.49 23.68 30.90 28.83 35.05 31.98 34.80 38.13 34.18 46.04 23.94 40.13 42.59 34.15 45.29 22.67 36.81 39.69 35.80 47.16 55.03 19.21 36.50 42.05 33.92 47.04 41.65 31.46 35.06 24.26 47.14 31.38 25.91 67.05 42.14 38.58 31.37 40.40 47.69 25.40 40.57 31.50 30.99 30.84 30.25 31.99 40.39 51.08 45.81 36.67 35.46
0.72 0.91 0.89 0.85 0.76 0.75 0.80 0.84 0.70 0.92 0.44 0.79 0.74 0.92 0.87 0.77 0.74 0.81 0.81 0.89 0.86 0.66 0.91 0.79 0.89 0.68 0.69 0.83 0.74 0.75 0.75 0.78 0.57 0.68 0.84 0.80 0.70 0.88 0.83 0.83 0.90 0.80 0.82 0.69 0.84 0.81 0.92 0.92 0.92 0.75 0.65 0.84 0.86 0.81 0.91 0.72 0.90 0.89 0.77 0.89 0.84 0.74 0.86 0.88 0.84 0.92 0.87 0.90 0.94 0.93 0.89 0.85 0.88 0.88 0.90 0.91 0.84 0.90 0.72
0.14 0.20 0.20 0.13 0.14 0.11 0.14 0.19 0.22 0.21 0.20 0.13 0.17 0.21 0.23 0.22 0.19 0.21 0.13 0.18 0.15 0.17 0.17 0.15 0.20 0.18 0.18 0.19 0.12 0.15 0.15 0.14 0.32 0.21 0.20 0.22 0.26 0.20 0.18 0.17 0.18 0.18 0.12 0.17 0.21 0.15 0.23 0.17 0.16 0.19 0.21 0.17 0.18 0.13 0.22 0.14 0.16 0.21 0.12 0.13 0.15 0.10 0.19 0.19 0.18 0.20 0.20 0.22 0.16 0.19 0.16 0.16 0.19 0.17 0.22 0.15 0.15 0.17 0.26
0.65 1.02 1.04 0.79 0.66 0.76 0.80 0.76 0.64 1.18 0.30 0.67 0.79 1.02 0.97 0.78 0.66 0.44 0.73 0.96 0.91 0.77 0.91 0.88 0.93 0.54 0.77 0.83 0.80 0.79 0.83 0.86 0.45 0.74 0.70 1.17 0.49 0.76 0.74 0.80 0.99 0.97 0.77 0.85 2.55 0.73 0.96 0.99 0.95 0.79 0.41 0.94 0.81 0.74 1.08 0.96 0.91 0.87 0.52 0.96 0.80 0.65 0.78 0.76 0.78 1.12 0.69 1.06 0.76 1.03 0.86 0.85 1.20 0.74 0.84 0.91 0.86 0.82 0.48
1.607 3.801 4.861 2.358 2.323 1.868 2.230 3.158 2.154 5.310 0.754 1.429 2.186 4.585 3.879 1.675 2.402 2.028 1.870 3.729 1.264 0.939 1.943 1.553 2.949 0.912 1.208 3.038 0.829 1.247 1.515 1.574 1.581 1.893 2.208 4.754 1.787 3.753 1.346 2.475 3.801 2.293 1.790 1.033 9.707 2.059 4.365 4.098 4.082 1.025 1.369 3.098 2.397 1.943 4.941 1.557 2.379 2.204 1.182 2.048 1.501 1.873 3.056 2.763 2.005 4.612 3.134 2.724 2.344 3.095 2.151 1.726 3.046 1.796 3.503 3.223 2.692 2.508 -
S148 S149 S150 S151 S152 S153 S154 S155 S156 S157 S158 S159 S160 S161 S162 S163 S164 S165 S166 S167 S168 S169 S170 S171 S172 S173 S174 SS1 SS2 SS3 SS4 SS5 SS6 SS7 SS8 SS9 SS10 SS11 SS12 SS13 SS14 SS15 SS16 SS17 SS18 SS19 SS20 SS21 SS22 SS23 SS24 SS25 SS26 SS27 SS28 SS29 SS30 SS31 SS32 SS33 SS34 SS35 SS36 SS37 SS38 SS39 SS40 SS41 SS42 SS43 SS44 SS45 SS46 SS47 SS48 SS49 SS50 SS51 SS52
PSYCHIATRY PSYCHOL PUBLIC, ENVIRONM & OCC GEN HEALTH RADIOL, NUCL MED & MED IMAG REHABILITAT REMOTE SENS REPRODUCTIVE BIOL RESPIRATORY SYST RHEUMATOL ROBOT SOIL SCI SPECTROSCOPY SPORT SCI STAT & PROBABIL SUBSTANCE ABUSE SURGERY TELECOM THERMODYN TOXICOL TRANSPLANT TRANSPORT SCI & TECH TROP MED UROL & NEPHROL VETERINARY SCI VIROL WATER RESOURCES ZOOL ANTHROPOL AREA STUDIES BUSINESS BUSINESS, FINANCE COMMUNICAT CRIMINOL & PENOL CULTURAL STUDIES DEMOGRAPHY ECON EDUC & EDUC RES EDUC, SPECIAL ENVIRONM STUDIES ERGONOM ETHICS ETHNIC STUDIES FAMILY STUDIES GEOGRAPHY GERONTOL HEALTH POLICY & SERV HIST HIST & PHILOS OF SCI HIST OF SOCIAL SCI HOSPITAL, LEIS, SPORT & TOUR INDUSTR RELAT & LABOR INFORMAT SCI & LIBR SCI INT RELAT LAW LINGUIST MANAGE NURS PLANN & DEV POLIT SCI PSYCHIATRY PSYCHOL, APPL PSYCHOL, BIOL PSYCHOL, CLIN PSYCHOL, DEV PSYCHOL, EDUC PSYCHOL, EXPT PSYCHOL, MATH PSYCHOL, MULTIDISCIP PSYCHOL, PSYCHOANAL PSYCHOL, SOCIAL PUBLIC ADM PUBLIC, ENVIRONM & OCC GEN HEALTH REHABILITAT SOCIAL ISSUES SOCIAL SCI, BIOMED SOCIAL SCI, INTERDISCIP SOCIAL SCI, MATH METH SOCIAL WORK SOCIOL
485603 211860 385850 481649 99117 51285 179750 240911 157097 20108 130188 178154 222816 138380 60317 747985 124425 132560 362715 134825 38432 75960 305917 354658 287583 246190 361803 90985 28124 196302 85960 52751 46888 4798 19467 324730 165628 36537 124336 26352 42523 11649 54465 79737 66854 89409 19717 24325 21007 48631 14563 63546 56150 149174 103509 257814 122147 51099 108435 299136 100878 59120 208588 151501 59230 237748 13641 196309 11231 115913 35026 242429 87309 24734 60793 81449 43700 45449 104512
576782 257868 519875 545932 124731 69054 198502 268308 174265 32676 161955 208226 264736 189435 73043 844558 197889 171792 433917 148395 64196 94259 339449 447730 307702 337415 460891 160999 81449 276839 117663 98905 80085 15095 36141 524600 310756 53139 226111 42035 71361 25591 84627 156234 90104 135784 66282 52861 50056 76963 27507 114676 121969 230820 180385 367462 187498 102847 233178 374398 140896 67642 270475 195736 87070 288157 18429 282212 17756 155782 71439 360171 123939 50252 92668 156009 63868 81617 222709
21
79435 25390 65623 85883 10646 7321 23610 45504 32264 3355 12098 26031 28069 16634 8049 120918 21791 17614 47847 27423 4341 10570 58233 31900 47242 30246 30040 6675 1537 14674 8184 4104 2842 268 1680 32935 12141 2612 13860 2807 3487 813 4028 7161 8758 13659 612 1540 675 2840 1076 7377 4307 9451 6186 20293 10510 4417 8219 45075 8445 5967 24720 17088 4686 25895 2087 20743 976 10135 2677 30097 6987 2550 7862 7010 4657 2937 7693
81974 28636 83835 91399 15214 9266 26713 46199 31641 4136 15840 32306 31732 18831 9739 123438 31501 21357 62011 27311 9395 15699 65473 49663 56952 46250 44346 16147 12555 24557 13133 11600 7873 1530 3791 61834 32501 5600 34232 4380 9109 2517 8513 19868 11599 21954 6263 4608 2684 6860 2967 16483 19684 41859 15290 28323 25955 12526 32227 50710 11509 7775 30799 19905 7415 30219 1792 29384 1773 14125 9244 50332 13096 6875 12707 16636 5666 8780 22281
0.54 0.54 0.60 0.56 0.65 0.55 0.54 0.53 0.56 0.60 0.52 0.50 0.58 0.53 0.54 0.56 0.55 0.56 0.54 0.51 0.60 0.64 0.51 0.53 0.56 0.55 0.53 0.57 0.74 0.57 0.60 0.65 0.67 0.59 0.64 0.69 0.66 0.65 0.53 0.55 0.81 0.63 0.61 0.54 0.61 0.78 0.60 0.71 0.97 0.72 0.57 0.63 0.59 0.78 0.64 0.67 0.59 0.62 0.56 0.53 0.53 0.55 0.55 0.58 0.56 0.49 0.58 0.47 0.56 0.64 0.66 0.64 0.55 0.55 0.63 0.57 0.68 0.60
47.13 51.79 35.30 34.00 38.16 33.12 44.88 38.69 39.81 29.23 44.37 32.72 37.59 26.86 49.29 28.51 21.95 27.94 46.25 30.50 23.77 33.26 35.21 32.16 48.09 35.51 46.65 58.42 45.71 61.33 38.18 47.39 52.86 41.58 45.98 36.42 46.32 48.80 50.81 40.77 45.83 46.78 48.41 58.80 44.13 37.07 66.28 52.91 65.09 61.92 42.85 38.89 48.10 62.20 55.06 63.55 36.47 48.33 46.49 47.75 57.51 57.76 49.03 53.26 52.17 51.19 33.51 49.04 44.84 49.99 50.31 39.61 45.35 37.14 42.65 43.20 33.54 49.40 53.82
0.84 0.82 0.74 0.88 0.79 0.74 0.91 0.90 0.90 0.62 0.80 0.86 0.84 0.73 0.83 0.89 0.63 0.77 0.84 0.91 0.60 0.81 0.90 0.79 0.93 0.73 0.79 0.57 0.35 0.71 0.73 0.53 0.59 0.32 0.54 0.62 0.53 0.69 0.55 0.63 0.60 0.46 0.64 0.51 0.74 0.66 0.30 0.46 0.42 0.63 0.53 0.55 0.46 0.65 0.57 0.70 0.65 0.50 0.47 0.80 0.72 0.87 0.77 0.77 0.68 0.83 0.74 0.70 0.63 0.74 0.49 0.67 0.70 0.49 0.66 0.52 0.68 0.56 0.47
0.17 0.14 0.22 0.19 0.15 0.18 0.15 0.19 0.20 0.21 0.12 0.18 0.14 0.14 0.16 0.17 0.25 0.16 0.17 0.20 0.24 0.21 0.21 0.14 0.20 0.19 0.12 0.18 0.45 0.13 0.15 0.22 0.17 0.32 0.19 0.19 0.20 0.15 0.28 0.17 0.21 0.22 0.16 0.25 0.17 0.25 0.32 0.19 0.13 0.14 0.20 0.26 0.35 0.28 0.15 0.11 0.21 0.25 0.30 0.17 0.11 0.13 0.15 0.13 0.13 0.13 0.13 0.15 0.16 0.12 0.26 0.21 0.15 0.28 0.21 0.20 0.13 0.19 0.21
0.97 0.89 0.78 0.94 0.70 0.79 0.88 0.98 1.02 0.81 0.76 0.81 0.88 0.88 0.83 0.98 0.69 0.82 0.77 1.00 0.46 0.67 0.89 0.64 0.83 0.65 0.68 0.41 0.12 0.60 0.62 0.35 0.36 0.18 0.44 0.53 0.37 0.47 0.40 0.64 0.38 0.32 0.47 0.36 0.76 0.62 0.10 0.33 0.25 0.41 0.36 0.45 0.22 0.23 0.40 0.72 0.40 0.35 0.26 0.89 0.73 0.77 0.80 0.86 0.63 0.86 1.16 0.71 0.55 0.72 0.29 0.60 0.53 0.37 0.62 0.42 0.82 0.33 0.35
3.507 2.741 2.666 2.972 2.103 1.948 2.904 3.475 4.133 1.795 1.721 2.065 2.300 1.241 2.959 2.272 1.331 1.608 2.765 2.876 0.957 2.400 3.078 1.213 4.122 1.764 1.613 1.381 0.640 1.845 1.602 1.271 1.260 1.258 1.459 1.242 1.574 2.027 1.436 1.232 1.203 1.449 1.644 2.335 2.271 0.479 0.922 0.623 2.212 1.208 1.430 1.078 1.495 1.471 2.249 1.367 1.233 1.011 3.215 1.812 2.682 2.459 2.572 1.637 2.590 1.840 2.098 1.147 1.835 1.199 2.177 1.632 1.043 2.002 1.227 1.392 1.201 1.111
SS53 SUBSTANCE ABUSE SS54 TRANSPORT SS55 URBAN STUDIES SS56 WOMEN'S STUDIES AIF of JCR (both editions) AIF of Science edition AIF of Social Science edition JCR average JCR standard deviation Science average Science standard deviation Social Science average Social Science standard deviation
61928 26648 36971 36072
83290 44866 71615 65185
6596 3392 3003 2381
261104
315665
42074
316816
372510
52894
87999
139039
8453
22
10506 5717 7577 6659
0.62 45.79 0.74 0.17 0.68 36.42 0.59 0.21 0.58 50.19 0.52 0.20 0.61 46.66 0.55 0.18
48080 0.57 0.07 58378 0.55 0.05 16080 0.62 0.09
39.88 10.69 37.18 10.01 48.28 8.09
0.75 0.14 0.80 0.10 0.60 0.13
0.18 0.05 0.18 0.04 0.20 0.07
0.63 0.59 0.40 0.36
0.74 0.25 0.82 0.21 0.50 0.22
2.261 1.874 1.211 1.048 2.822 2.920 1.848 2.258 1.183 2.473 1.248 1.585 0.562
Figure 1: Aggregate Impact Factor of the JCR subject categories (in decreasing order) 10
Aggregate Impact Factor
8
6
4
2
0 1
21
41
61
81
101
121
JCR Subject Categories Science
23
Social Science
141
161
Table 2: Cluster Analysis of the JCR categories according to the AIF components Level
Cluster
# Categories
Science categories
Social Science categories
L1
C1
29
2, 5, 32, 33, 34, 36, 38, 45, 50, 61, 77, 85, 86, 94, 103, 105, 119, 164, 168, 169, 173
9, 13, 19, 30, 42, 45, 48, 54
79
1, 5, 6, 8, 10, 11, 14, 15, 16, 21, 24, 28, 46, 49, 51, 52, 55, 56
101
25, 47
-
12, 17, 26, 27, 31, 32, 44
3, 7, 10, 14, 15, 18, 19, 20, 22, 23, 25, 26, 27, 28, 29, 30, 39, 46, 48, 49, 51, 55, 65, 70, 71, 76, 78, 82, 83, 88, 91, 93, 96, 104, 106, 108, 109, 110, 115, 116, 120, 123, 131, 132, 134, 135, 136, 137, 138, 141, 143, 148, 150, 151, 155, 156, 163, 166, 167, 170, 172
18, 33
1, 4, 6, 12, 24, 31, 35, 37, 40, 41, 42, 47, 52, 53, 54, 56, 57, 58, 60, 62, 64, 68, 80, 81, 84, 89, 90, 92, 95, 97, 98, 99, 100, 102, 112, 114, 118, 121, 124, 125, 126, 128, 129, 133, 139, 140, 142, 146, 152, 153, 157, 159, 160, 161, 165, 171
4, 40, 50
8, 9, 13, 16, 44, 67, 69, 72, 73, 74, 75, 87, 111, 122, 127, 130, 144, 145, 149, 154, 158, 162, 174
3, 29, 34, 35, 36, 37, 38, 39, 41, 43, 53
11, 43, 66, 117
-
107
22, 23
17, 21, 59, 63, 113, 147
2, 7, 20
(12.61%) C2
19 (8.26%)
C3
3 (1.30%)
C4
7 (3.04%)
C5
63 (27.39%)
C6
59 (25.65%)
C7
34 (14.78%)
C8
4 (1.74%)
C9
3 (1.30%)
Non clustered L2
C10
9 (3.91%) 48
C1, C2
(20.87%) C11
10
C3, C4
(4.35%) C12
160
C5, C6, C7, C8
(69.56%)
24
Table 3: Correlations between the main variables and Principal Component Analysis (t=2010) Science subject categories |F| AtF |F| At F
Rt F
JtF
0.67
0.72
atF
0.90
0.93
rtF
1.00
0.95
0.98
ptF
1
0.96
0.99
wtF
1
0.98
btF
1
AIFtF
1 0.81 0.79 0.75 1
Rt F
0.94 0.93 1
JtF
NCitedtF NCitingtF
NCitedtF NCitingtF
atF
rtF
ptF
wtF
btF
AIFtF
1
0.02
0.03
0.08
-0.11
0.14
1
0.40
-0.21
0.14
0.52
1
-0.20
0.55
0.65
1
-0.03
0.24
1
0.76 1
PCA 0.2060 0.0731 0.3655 0.2093 0.1460 scores
Social Science subject categories |F| AtF |F| At F Rt F JtF NCitedtF NCitingtF
Rt F
JtF
0.66
0.85
atF
0.87
0.94
rtF
0.97
0.89
0.95
ptF
1
0.95
0.91
wtF
1
0.87
btF
1
AIFtF
1 0.90 0.90 0.80 1
0.96 0.92 1
NCitedtF NCitingtF
atF
rtF
ptF
wtF
1
0.29
-0.50
0.25
-0.56 -0.26
1
-0.15
-0.11
-0.29 -0.01
1
-0.71
0.88
1
btF
0.85
-0.68 -0.48 1
PCA 0.1173 0.0220 0.0478 0.5779 0.2350 scores
25
AIFtF
0.78 1
Figure 2: Scatter plot of the components with the Aggregate Impact Factor Science
Social Science
12,000
3,500
y = 3,5262x + 0,5277 2 R = 0,0207
2,500 AIF
AIF
8,000 6,000 4,000
2,000 1,500 1,000
2,000 0,000 0,00
y = -1,7146x + 2,6491 2 R = 0,0673
3,000
10,000
0,500
0,10
0,20
0,30
0,40
0,50
0,60
0,70
0,80
0,000 0,00
0,90
0,20
0,40
Field growth rate
12,000
0,80
1,00
3,500
y = 0,0672x - 0,0107 2 R = 0,2687
1,20
y = -0,0009x + 1,6308 2
R = 0,0002
3,000
10,000
2,500 AIF
8,000 AIF
0,60 Field growth rate
6,000
2,000 1,500
4,000
1,000 2,000 0,000 0,00
0,500
10,00
20,00
30,00
40,00
50,00
60,00
70,00
0,000 0,00
80,00
10,00
20,00
Average number of references
12,000
40,00
50,00
60,00
3,500
y = 7,7528x - 3,7381 R2 = 0,4246
10,000
3,000
8,000
2,500
6,000
AIF
AIF
30,00
70,00
Average number of references
y = 3,9755x - 0,8311 R2 = 0,7281
2,000 1,500
4,000
1,000 2,000
0,500 0,000 0,00 -2,000
0,10
0,20
0,30
0,40
0,50
0,60
0,70
0,80
0,90
0,000 0,00
1,00
0,10
0,20
0,30
Ratio of references to JCR items
12,000
0,50
0,60
0,70
0,80
3,500
y = 8,3538x + 0,9683 R2 = 0,0561
0,90
1,00
y = -4,1249x + 2,3899 R2 = 0,2288
3,000
10,000
2,500 AIF
8,000 AIF
0,40
Ratio of references to JCR items
6,000
2,000 1,500
4,000
1,000 2,000 0,000 0,00
0,500
0,05
0,10
0,15
0,20
0,25
0,30
0,000 0,00
0,35
0,05
0,10
Ratio of JCR references to the target window
0,20
0,25
0,30
0,35
0,40
0,45
0,50
Ratio of JCR references to the target window
3,500
y = 4,5613x - 1,2595 2 R = 0,5788
10,000
3,000
8,000
2,500
6,000
AIF
AIF
12,000
0,15
4,000
y = 2,0506x + 0,5513 2 R = 0,6083
2,000 1,500 1,000
2,000
0,500 0,000 0,00 -2,000
0,50
1,00
1,50
2,00
2,50
0,000 0,00
3,00
0,20
0,40
0,60
0,80
1,00
Proportion of cited to citing items in the target window
Proportion of cited to citing items in the target window
26
1,20
1,40
Table 4: Frequency of the components (m=mean, s=standard deviation) Science frequency Social Science frequency Interval atF rtF ptF wtF btF atF rtF ptF wtF btF (-,m-3s) 0 0 2 0 0 0 0 0 0 0 [m-3s,m-2s) 3 1 8 1 2 0 0 2 0 0 [m-2s,m-s) 10 28 17 15 13 2 10 5 3 7 [m-s,m) 67 63 44 60 76 28 19 20 28 25 [m,m+s) 64 58 66 71 71 18 17 19 17 13 [m+s,m+2s) 20 19 37 23 11 5 8 9 6 10 [m+2s,m+3s) 7 4 0 2 0 1 2 1 1 0 [m+3s,-) 1 1 0 2 1 1 0 0 1 1 [m-s,m+s] 76.16% 69.54% 63.22% 75.29% 84.48% 83.64% 64.29% 69.64% 80.36% 67.86% [m-2s,m+2s] 93.60% 96.55% 94.25% 97.13% 98.28% 96.36% 96.43% 94.64% 96.43% 98.21% [m-3s,m+3s] 99.42% 99.43% 98.85% 98.85% 99.43% 98.18% 100.00% 100.00% 98.21% 98.21%
Figure 3: Frequency histograms of the components (m=mean, s=standard deviation) Science 80 70
(-,m-3s)
60
[m-3s,m-2s)
50
[m-2s,m-s) [m-s,m)
40
[m,m+s)
30
[m+s,m+2s)
20
[m+2s,m+3s) [m+3s,-)
10 0 a
r
p
w
b
Social Science 30 25
(-,m-3s) [m-3s,m-2s)
20
[m-2s,m-s) [m-s,m)
15
[m,m+s) [m+s,m+2s)
10
[m+2s,m+3s) [m+3s,-)
5 0 a
r
p
w
27
b
Figure 4: CNIF of all journals in the economics and business field
Figure 5: CNIF of all journals in two or more categories of the economics and business field
28
