1 Introduction

Before 1980s, the information and knowledge were stored in printed documents. These documents are evaluated, collected, stored and retrieved from library and information centres in which different measures like abstracting, indexing, consolidation, repackaging etc. are applied in order to arrange and retrieve documents. However, these complicated mechanisms are difficult for users to understand and use. On other hand, finding the required information was very difficult due to lack of channels of communications, high cost and less precision and recall. For proper access to required information, library professionals used to provide user education to instruct and guide users. Recently, the advancement of ICT, improvements in sophisticated infrastructures, and use of digital devices and internet etc. have laid information overpopulation. Notwithstanding, the opportunities of ease in access to information come with the challenges to sort and select the right and quality information. Due to easy and flexible access to huge amount of information via variety of applications and channels used to process and distribute, the users are facing challenges to retrieve right information at right time from right source. It is required to be able not only to search the required information but also to evaluate the relevance, accuracy, reliability, and currency of the information and the source. The skills and knowledge to locate, retrieve, evaluate, and use relevant information constitutes information literacy (IL). Julien and Barker (2009) defined the term "information literacy" is as the set of skills required to identify information sources, access information, evaluate it, and use it effectively, efficiently, and ethically (Julien & Barker, 2009).

In present information society, everyone, from novice to expert, from layman to professional, from students/researchers to professors, from farmers to scientists, from buyers to lawyers, from bankers to businessmen, and from politicians to army, are required to be informed. Information became worth and wealth. One who is information literate have more powers than others. On other hand, individuals having no IL Skills have lack of information, dependency upon others to get information, and even to acute levels of information anxiety. IL is important due to its potentiality to optimize the use of available information and to transform the novice into self-directed lifelong learners. Thus, information literacy skill is required by all concerned with every quantum of knowledge worldwide like from farming and horticulture to business and commerce, from aviation to shipping, from banking to life insurance, from health care to court of law (Majumdar & Singh, 2007). IL researchers and practitioners are engaged in development of models, designs, tools, standards, guides and frameworks, course instructions, etc. for enhancing IL skills as well as evaluation, assessment and impact of these in every subject fields. The IL research publications are spread out in large number of major and minor disciplines. The present paper employs co-occurrence network analysis to examine the evolution, current trend and research gaps in respect of disciplines engaging in global IL research and practice as well as intellectual base of IL publications. The finding of the study might be beneficial not only for global perspectives of IL research, but also for librarians, researchers, practitioners and policy makers in order to planning for assessment and provision of IL for those concerned with any segment of world of knowledge.

2 Review of Literature

Bruce (2004) stated information literacy as "a natural extension of the concept of literacy in our information society, and information literacy education is the catalyst required to transform the information society of today into the learning society of tomorrow" (Bruce, 2004). Information literacy comes with several other literacies which are individually or collectively used for IL viz., computer literacy, digital literacy, hyper-literacy, information technology literacy, interactive literacy, Internet literacy, library literacy, media literacy, multiple literacy, network literacy, oral literacy, and visual literacy etc. (Bawden, 2001; Dhiman, 2006). The critical review of the IL publications in different disciplines is imperative for the present study. At the same line, Ferguson et al. (2016) assessed IL competence of biology students (Ferguson, Neely, & Sullivan, 2016) and recognized the importance of awareness about IL among students. Moreover, the same is assessed in the field of Agricultural Sciences (Singh, 2015), Engineering (Alii & Abu-hassan, 2009), Library and Information Science (Islam & Tsuji, 2010), and Biosciences (Biradar & Swapna, 2011) etc. Similarly, IL competence is found vital ability for professionals related to Medical Profession (Lata & Sharma, 2013), Management (Kirk, 2004), Disability (Nanda & Ramesh, 2012), Pharmaceutics (Bawden, Devon, & Sinclair, 2000), Company Audit (Cheuk, 2000), Statistics (Cliftlands, 2005), Firefighting (Lloyd, 2005).

Based on the classification of subject categories in the Journal Citation Report of WoS, Hariri, Shekofteh and Yekta (2008) conducted subject category co-citation network analysis of journals publishing medical sciences in Iran and concluded the strong relationship between Multidisciplinary Sciences and Medical Sciences (Hariri, Shekofteh, & Yekta, 2008). However, Yao et al. (2013) visualized the subject category co-occurrence network of publications of translational medical research and examined the graph-theoretical property of nodes and found Research & Experimental Medicine, Medical Laboratory Technology, General and Internal Medicine is outstanding. Meanwhile, Oncology, Neurosciences & Neurology, Pharmacology & Pharmacy, Cell Biology, Biochemistry & Molecular Biology, Immunology in most central position and playing key role in the development of translation medical research (Yao, Lyu, Ma, Yao, & Zhang, 2013). Similarly, Zhu and Guan (2013) critical examined the subject category co-occurrence network of innovative research and found 48 subject categories in the field in which Business and Economics, Engineering, Public Administration, Operations Research and Management Science, and Computer Science are recognized as the core subjects (Zhu & Guan, 2013). Consequentially, Yao et al. (2014) analysed subject categories co-occurrence network of the Health System Research publications and recognized Public, Environmental and Occupational Health, Health Care Sciences and Services, and General & Internal Medicine as core subjects while nursing, pharmacology and pharmacy, and surgery are also playing key role in the research field (Yao et al., 2014). Moreover, subject co-occurrence network analysis is also applied in Innovation System Research (Z. Liu, Yin, Liu, & Dunford, 2015), Agriculture (Bartol, Budimir, Juznic, & Stopar, 2016), and Global Value Chains (GVC) (L. Liu & Mei, 2016).

3 Data and Methodology Applied

3.1 Data Set

Besides of various data gathering techniques like questionnaires, interviews, observations, archival records, experiments, etc., archival records are most suitable for the studies based on both scientometrics and social network analysis (SNA) due to less labor-intensive and least confusing (Milojevic, 2014). Thus, data collected from records archived in bibliographic databases are found purposeful for the study. In this regard, within top three bibliographic databases viz. Web of Science (WoS) of Thomas Reuters, Scopus of Elsevier, and Google Scholar from Google, Scopus is claimed as the largest abstract and citation database of peer-reviewed literature e.g. scientific journals, books and conference proceedings ("About Scopus," n.d.). It is an international multidisciplinary database indexing over 19000 international peer reviewed journals in all subjects, besides more than 500 international conference/seminar proceedings. Due to its wider coverage to the work of knowledge, Scopus data is assumed to generate a better picture of IL literature in the global context and hence found suitable for this study (Gupta & Dhawan, 2009).

Since, IL is used for same concept with several other names worldwide. In order to get full coverage of the IL research and practice literature, we opted advance search method to retrieve IL research articles published during 2001-16. The search string used is:

(TITLE) "information literacy" or "digital literacy" or "media literacy" or "computer literacy" or "infoliteracy" or "informacy" or "information empowerment" or "Information competency" or "information competence" or "information handling" or "information fluency" or "information mediacy" or "information mastery") AND PUBYEAR > 2000 AND PUBYEAR < 2017)

Total of 3859 records having information literacy or its synonymous words in article title are collected in which 3853 records are found suitable for the present study. Figure 1 shows year wise growth of IL publications with trend line in linear regression with R2 = 0.955 which is the best fit and enough to depict the linear growth of the IL publications in future. Hence, the data retrieved from the Scopus database is found suitable for the study.

3.2 Discipline Co-Occurrence Network Analysis

The disciplinary composition of a given research field reveals extent to which the research field is shaped by confluence of disciplines and their respective roles (Ji, Liu, & Zhao, 2015). It can be used to describe the intellectual structure of subject areas by means of mutual relations between subject fields and referred as discipline co-occurrence analysis (L. Liu & Mei, 2016), subject co-classification analysis (Bordons, Morillo, & Gomez, 2004) and more specific in case of WOS data as Subject Category co-occurrence analysis (Yao et al., 2014, 2013). Such studies are based on the classification terms used by the databases to classify the documents published in different sources and channels of communications. These sources are classified by classification schemes adopted by databases.

Particularly, the classification scheme of Scopus database is used to classify the whole world of knowledge into 27 major subject areas which are represented alphabetically in table 1. Each and every document is assigned one or more subject areas according to the context of the source in which these are published. These subject areas are minutely observed for analysis and interpretation of the present study.

3.4 Mapping and Visualization of Network

According to the subject area wise distribution of IL publications, a matrix of citing and cited subject areas are drawn manually and furthermore network file is created for use in mapping and visualization of subject areas co-occurrence network with the help of BibExcel ("BibExcel," 2016; Persson, Danell, & Schneider, 2009). Pajek (de Nooy, Marvar, & Batagelj, 2005), an exploratory network analysis tool, is used for mapping and visualization of network along with VOSviewer (Van Eck & Waltman, 2010, 2014). Different centrality measures are calculated through Pajek (Batagelj & Mrvar, 2003). According to Freeman (1979), centrality is an important structural factor influencing leadership, satisfaction, and efficiency (Abbasi, Hossain, & Leydesdorff, 2012).

3.5 Limitations

The present study is limited to the worldwide research papers which have Information Literacy or its synonymous words in the title published during the time period of 2001-2016. The subject analysis is fully based on the subject areas assigned by Scopus according to its own subject classification scheme. Macro level and micro level measures of Social Network analysis are applied in order to get insight from discipline co-occurrence network analysis.

4 Data Analysis and Interpretation

4.1 Ranking of Subject Areas

The ranking of subject areas in descending order of the IL publications, as shown in table 2 and figure 2, depicts that Social Sciences (2917) have highest number of IL publications while Veterinary (1) have least number of publications. Furthermore, the research gap is observed in the field of Immunology and Microbiology. In addition, it is interesting to observe that only 6 subject areas viz. Social Sciences; Computer Science; Arts and Humanities; Engineering; Medicine; Business, Management and Accounting constitutes more than 90% of IL literature (see fig 2) while other subject areas includes less than 10 %. It is also worth noting that 3859 publications related to information literacy have 5373 frequencies in the subject areas which indicates the presence of interconnections between the subject areas i.e. some publications have presence in more than one subject areas.

4.2 Temporal Intellectual Progress of IL Research

The temporal distribution of subject areas wise IL publications during the research period as illustrated in table 3 and figure 3 is reveals the intellectual progress of IL research in different subject areas. This analsys clearly shows the dominance of Social Sciences followed by Computer Science, and Art and Humanities in the research field throughout the research period (see figure 3). From figure 2 and figure 3, It can be observed that the IL reasearch and practices surround aound the Social Sciences which includes Library and Information Science as a subject. However, Computer Science have prevalent literature on information literacy.

4.3 Subject Area Co-Occurrence Network Analysis

Liu et al. (2015) states that "co-occurrence analysis is based on the assumption that when two items appear in the same context, they are related to some degree" (Z. Liu et al., 2015). At this point, it can be expected that when two subjects appear in same article, they are related to some degree in the context of the article. Therefore, analysis of subject area co-occurrence network is the proxy of the subject co-occurrence which is significant in the detection of the disciplines involved in the development of intellectual structure of IL research and practices and can be visualized by social network analysis tools. Several measures of SNA like centrality measures i.e. degree, closeness and betweenness etc. can be applied in order to get close insights about the relatedness of the subjects in the specific research domain.

An undirected network is mapped and visualized with the help of Pajek and VOSviewer and represented in figure 4. Each node in the network represents a subject area, on other hand, each link represents the interconnection between subject areas involved IL research. The size of the nodes as shown in figure 4 are proportional to its link strength and colour of node reflects the clusters of nodes representing the affinity to interconnection to each other. In the meanwhile, the width of links are proportional to degree of relatedness. The details about macro level SNA measures of the network is illustrated in table 4.

As previously discussed, the present study is focused on the three basic centrality measures proposed by Freeman i.e. degree, closeness, and betweenness centrality measures for both point centrality and graph centrality i.e. micro level and macro level study.

4.3.1 Macro Level Analysis

Macro level analysis is also referred as network level analysis. The co-occurrence network of subject areas involved in IL research consist of 26 nodes which are interconnected with 105 links. It means that 26 out of 27 subject areas of Scopus database are linked to one another to form the network for intellectual base of IL research (see table 4). The network has only one component i.e. giant component of 100 % ratio. At this situation, the subject areas are linked to form a connected graph. Since, high density of network is indicator of high degree of knowledge flow in the nodes. The density (32.3%) of the network shows less density of the network and lower degree of knowledge flow.

The degree centrality of a network acts as indicator of the level of centralization of nodes in the network and its collaboration rate. As mentioned in table 4, average degree centrality of the network (8) reveals 8 publications per subject area in whole network which show degree of centralization of subjects in the network and degree of relatedness. The feasibility of more co-occurrences among subjects is expected. 63.7% of closeness centrality of the network affirms that subjects are close to central node for knowledge sharing. Further, betweenness centrality of a network indicates the strength of ties among the nodes. In this context, the betweenness measure is relevant to provide insights about the relations among subjects in the sense of interdisciplinarity. In this analysis, 32.3% of average betweenness centrality is observed at the network level.

4.3.2 Micro Level Analysis

Micro level analysis is also referred as the node level analysis. At this level, the nodes and its features are analysed according to various metrics of social network analysis. In the present study, centrality measures (Freeman, 1978; Newman, 2001; Wasserman & Faust, 1994) like degree, closeness, betweenness and eigenvector are applied to get insight. Ranking of subject areas according to above mentioned four centrality measure has been attempted and shown in table 5.

Measuring the degree centrality of a node is also referred as point centrality measure (Freeman, 1978) and local centrality (Scott, 2000). Freeman (1978) described that an actor with high degree centrality in the network can withhold or distort the information flow in the group because of its role and position with strong relationship in the group (Abbasi et al., 2012). Thus, a node with high degree centrality can be considered as leader or broker in the group (Krackhardt, 2010).

Degree centrality based visualization of the subject co-occurrence network is sketched and provided in figure 5. The size of each node is proportional to the value of degree centrality of the respective subject area, and the colour of nodes are according to the cluster. The modes having same degree centrality have same colour and size. The line between two subject areas indicates the co-occurrence or relationship. The ranking of subject areas according to its degree centralities shows that Social Sciences (23) followed by Computer Science (18), and Engineering (16) have highest degree centralities and can be recognized as leaders in the network. On other hand, Veterinary (1) has least degree centrality (see figure 5).

Further, closeness centrality is significant to assess the extent of independence of a node. Since, a node closer to all other nodes in the network does not depend on any node to access everyone (Zhang, 2010). Higher closeness centrality indicates greater ability to be heard more quickly in the network. Therefore, closeness centrality is proxy of efficiency for communicating with other nodes in the network (Abbasi et al., 2012). On other hand, Leydesdorff (2007) reported that closeness centrality measures fail to demonstrate the interdisciplinary aspects of journal ranked by subject categories (Leydesdorff, 2007) but it is obvious to show the central position of subject areas in the subject co-occurrence network. Table 5 depicts Social Sciences (.8929) is the top ranked subject areas lies on most central position in the network followed by Computer Science (.7813), Engineering (.7353), and Medicine (.7143).

Betweenness centrality, introduced by Linton C. Freeman (1977), measures the capacity of a node to help to connect components of a network otherwise that would be disconnected whether the node is removed. Accordingly, a node with high betweenness centrality acts as communicator as well gatekeeper that has power to control the information passes between others. It acts as intermediary between components (Bender et al., 2015; Van Eck & Waltman, 2014). As a further matter, it is the measure of the number of shortest paths in a network that passes through a node. It takes into account the connectivity of the node's neighbors by giving a higher value for nodes which bridge clusters (Ilhan, Gunduz-Oguducu, & Etaner-Uyar, 2014). Social Sciences (0.3412) followed by Engineering (0.1096), and Computer Science (0.1064) have highest betweenness centralities and can be recognized as communicators and gatekeepers in the network.

4.4 Ranking of Subject Area Co-Occurrences

An attempt has been made to analyse and rank co-occurrences of subject areas in consequence of intellectual structure of IL Publications during the research period. The result of this analysis is shown in table 7 for top 20 co-occurrences. Besides, the visualization of edge weight subject area co-occurrence network of IL publications is shown in figure 6. The width of the links in figure 6 is relative to the frequency of co-occurrences between nodes.

Clearly from table 6 and figure 6, the co-occurrence between Social Sciences and Computer Science (509) have highest value followed by Social Sciences--Arts and Humanities (265); Social Sciences--Business, Management and Accounting (114); and Social Sciences--Medicine (94). Out of top 20 co-occurrences, ten co-occurrences includes Social Sciences as one subject area. Thus Social Sciences is the core subject area of IL publications.

5 Summary and Conclusion

The information literacy research articles published during 2001-16 is spread out in 26 subject areas of Scopus database while the research gap is observed in only one subject area viz. Immunology and Microbiology. Larger frequency of publications in subject areas than the actual publications is significant to deduce the existence of co-occurrence of publications in more than one subject areas. More general, subject areas of Social Sciences, Computer Sciences, Arts and Humanities, Engineering, and Medicine are playing key role in IL research and practices. The temporal analysis of subject areas reflects the growing trend in IL publications in each subject area, however, fast growth is observed in Social Sciences, Computer Science, and Arts and Humanities.

Specifically, Social Sciences is recognized as core subject area of IL not only having largest contributions but also leads in the network. Social Sciences lies in most central position in the network, so efficient to communicate quickly to others. Social Sciences is also acting as the communicator and gatekeeper in the network. Obviously, Social Sciences control the knowledge flow in the network. It means every new idea in the network is communicated through this. On other hand, Computer Science, Engineering and Medicine have remarkable position in the network after Social Sciences. Surprisingly Arts and Humanities having third position in the ranking of subject areas according to IL publications shows much lower position in the ranking of different centrality measures of subject area co-occurrence network (see table 2, figure 2 and table 5). Highest co-occurrences are observed in Social Sciences and Computer Science followed by Social Sciences--Arts and Humanities; Social Sciences--Business, Management and Accounting; and Social Sciences-Medicine. Consequentially, out of top 20 co-occurrences, ten co-occurrences include Social Sciences as one subject area.

Future Research

Subsequent amount of co-occurrence of subject areas and diversity of publications in different subject areas are sign of interdisciplinary characteristics of IL publications. Thus, the interdisciplinary characteristics of IL publications can be examined.

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Punit Kumar Singh

Librarian

CMP Degree College, Allahabad -211002

(A Constituent PG College of Central University of Allahabad, Allahabad)

E-mail: punitbhu@gmail.com

Orcid ID: httDs://orcid.org/0000-0003-0266-1075

Scopus Author ID: 57197872928

&

Dr. Ajay P. Singh

Professor, Department of Library and Information Science

Banaras Hindu University, Varanasi-221005

E-mail: apsingh 73@yahoo.com

Punit Kumar Singh

Banaras Hindu University, punitbhu@gmail.com

Prof. Ajay P. Singh

Banaras Hindu University, apsingh_73@yahoo.com

Caption: Figure 1. Year Wise Distribution of IL Publications

Caption: Figure 3. Evolution of IL Publications in Different Subject Areas

Caption: Figure 4. Visualization of Subject Area Co-Occurrence Network of IL Publications

Caption: Figure 5. Degree Centrality Visualization of Subject Area Co-Occurrence Network of IL Publications

Caption: Figure 6. Edge Weight Visualization of Subject Area Co-Occurrence Network of IL Publications

Table 1. Alphabetical List of Subject Areas Used To Classify Documents
in Scopus Database

S. No.    Subject Area

1         Agricultural and Biological Sciences
2         Arts and Humanities
3         Biochemistry, Genetics and Molecular Biology
4         Business, Management and Accounting
5         Chemical Engineering
6         Chemistry
7         Computer Science
8         Decision Sciences
9         Dentistry
10        Earth and Planetary Sciences
11        Economics, Econometrics and Finance
12        Energy
13        Engineering
14        Environmental Science
15        Health Professions
16        Immunology and Microbiology
17        Materials Science
18        Mathematics
19        Medicine
20        Multidisciplinary
21        Neuroscience
22        Nursing
23        Pharmacology
24        Physics and Astronomy
25        Psychology
26        Social Sciences
27        Veterinary

Table 2. Ranking of Subject Areas According to IL Publications during
2001-16

Rank         Subject Areas                        No. of        % of
                                               Publications     5373

1       Social Sciences                            2917        54.290
2       Computer Science                           1042        19.393
3       Arts and Humanities                         299         5.565
4       Engineering                                 242         4.504
5       Medicine                                    238         4.430
6       Business, Management and Accounting         148         2.755
7       Psychology                                  94          1.749
8       Nursing                                     65          1.210
9       Health Professions                          59          1.098
10      Mathematics                                 53          0.986
11      Decision Sciences                           38          0.707
12      Economics, Econometrics and Finance         30          0.558
13      Chemistry                                   26          0.484
14      Biochemistry, Genetics and Molecular        24          0.447
        Biology
15      Agricultural and Biological Sciences        15          0.279
16      Multidisciplinary                           13          0.242
17      Environmental Science                       12          0.223
18      Earth and Planetary Sciences                11          0.205
19      Chemical Engineering                        10          0.186
20      Neuroscience                                 8          0.149
21      Pharmacology, Toxicology and                 8          0.149
        Pharmaceutics
22      Dentistry                                    7          0.130
23      Energy                                       5          0.093
24      Materials Science                            5          0.093
25      Physics and Astronomy                        3          0.056
26      Veterinary                                   1          0.019
        Total                                      5373

Table 3. Scopus Subject Area Wise Distribution of IL Publications
during 2001-16

S.No. *    2001    2002    2003    2004    2005    2006

1                             1       1
2             2       7       2      10       2      11
3                             2       1       2
4             1       1       3       3       8       8
5
6
7             2      14      10      10      34      44
8                     1                       6       3
9                     1                       1       1
10                            1               1
11                                            1
12
13            4       4       4      11       8      15
14                                            1
15                    1               2       3       6
16
17            2
18                    1       2       3       2       2
19            1       3      10       5      10      22
20
21            1                               1
22            2       2       3       3       5       5
23                                            1
24
25            3               3      19       2       3
26           45      68      83      89     117     102
27

S.No. *    2007    2008    2009    2010    2011    2012

1                                    11       5       1
2            13      10      22       8      10      25
3             5       4               2       1       1
4            14      13       5      11      11      14
5
6             1                       2       1       1
7            61      46      77      93      76      51
8                     4       2       4       2       2
9             1               2                       1
10            2       2                       1       1
11                                    2               3
12                                    2
13            5      13      10      23      26      15
14                    1       1
15            6       7       6       3       5       3
16
17                                    1       1       1
18            3       5       4               1       4
19           14      17      23      20      24      20
20                    1                       2       1
21                            1               1
22            1       4       5       8       5       3
23                            1               1
24                                                    1
25                    6       9      10       3       5
26          127     165     242     226     232     225
27                                            1

S.No. *    2013    2014    2015    2016

1             3               1       2
2            50      29      24      74
3             5               1
4            10      10      23      13
5                                    10
6                             4      17
7           136     113     137     138
8             4       3       2       5
9
10                    2               1
11            1       6      15       2
12            1                       3
13           33      28      21      22
14                    1       1       7
15            2       6       5       4
16
17
18            1       5      11       9
19           13      21      15      20
20            3       1       4       1
21                    1       1       2
22            6       3       7       3
23                            1       4
24                            1
25            5       9       4      13
26          282     270     304     340
27

* S. No. of table 1 for subject areas is used.

Table 4. Macro Level SNA Measures of Subject Co-occurrence Network

SNA Measures                          Output

Type of Network                    Undirected
Number of Nodes                    26
Number of Links                    105
Density                            0.3230
No. of Components                  1
Size of Giant Component            26 (100%)
Average Degree Centrality          8.0769
Average Closeness Centrality       0.6370
Average Betweenness Centrality     0.3234

Table 5. Centrality Measures of Subject Area Co-Occurrence Network of
IL Publications

Rank                 Rank by Degree Centrality

                            Subject Area                         DC

1       Social Sciences                                          23
2       Computer Science                                         18
3       Engineering                                              16
4       Medicine                                                 15
5       Agricultural and Biological Sciences                     13
6       Arts and Humanities                                      11
7       Mathematics                                              10
8       Environmental Science                                     9
9       Psychology                                                8
10      Business, Management and Accounting                       8
11      Health Professions                                        8
12      Biochemistry, Genetics and Molecular Biology              7
13      Materials Science                                         7
14      Earth and Planetary Sciences                              7
15      Energy                                                    6
16      Economics, Econometrics and Finance                       6
17      Decision Sciences                                         6
18      Nursing                                                   6
19      Chemistry                                                 5
20      Pharmacology, Toxicology and Pharmaceutics                5
21      Physics and Astronomy                                     4
22      Neuroscience                                              4
23      Chemical Engineering                                      3
24      Multidisciplinary                                         2
25      Dentistry                                                 2
26      Veterinary                                                1

Rank                Rank by Closeness Centrality

                            Subject Area                         CC

1       Social Sciences                                        0.8929
2       Computer Science                                       0.7813
3       Engineering                                            0.7353
4       Medicine                                               0.7143
5       Agricultural and Biological Sciences                   0.6757
6       Arts and Humanities                                    0.641
7       Environmental Science                                  0.6098
8       Psychology                                             0.5952
9       Business, Management and Accounting                    0.5952
10      Health Professions                                     0.5952
11      Earth and Planetary Sciences                           0.5814
12      Biochemistry, Genetics and Molecular Biology           0.5682
13      Economics, Econometrics and Finance                    0.5682
14      Decision Sciences                                      0.5682
15      Energy                                                 0.5682
16      Mathematics                                            0.5682
17      Pharmacology, Toxicology and Pharmaceutics             0.5556
18      Nursing                                                0.5556
19      Physics and Astronomy                                  0.5435
20      Chemistry                                              0.5435
21      Materials Science                                      0.5319
22      Neuroscience                                           0.5102
23      Chemical Engineering                                   0.4902
24      Dentistry                                              0.4902
25      Veterinary                                             0.4808
26      Multidisciplinary                                      0.4545

Rank               Rank by Betweenness Centrality

                            Subject Area                         BC

1       Social Sciences                                        0.3412
2       Engineering                                            0.1096
3       Computer Science                                       0.1064
4       Medicine                                               0.0726
5       Agricultural and Biological Sciences                   0.0409
6       Arts and Humanities                                    0.0395
7       Mathematics                                            0.0162
8       Environmental Science                                  0.0076
9       Psychology                                             0.0074
10      Health Professions                                     0.0058
11      Biochemistry, Genetics and Molecular Biology           0.0055
12      Business, Management and Accounting                    0.0048
13      Materials Science                                      0.0044
14      Chemistry                                              0.0043
15      Energy                                                 0.0043
16      Earth and Planetary Sciences                           0.0043
17      Nursing                                                0.0043
18      Physics and Astronomy                                  0.0037
19      Decision Sciences                                      0.0032
20      Neuroscience                                           0.0007
21      Chemical Engineering                                      0
22      Economics, Econometrics and Finance                       0
23      Pharmacology, Toxicology and Pharmaceutics                0
24      Veterinary                                                0
25      Dentistry                                                 0
26      Multidisciplinary                                         0

Table 6. Ranking of Top 20 Subject Area Co-Occurrences

Rank    Co-Occurrences                                    Frequencies

1       Social Sciences-Computer Science                      509
2       Social Sciences--Arts and Humanities                  265
3       Social Sciences--Business, Management and             114
        Accounting
4       Social Sciences--Medicine                              94
5       Social Sciences--Engineering                           91
6       Social Sciences--Psychology                            65
7       Medicine--Health Professions                           56
8       Computer Science-Engineering                           47
9       Computer Science-Mathematics                           45
10      Computer Science-Arts and Humanities                   27
11      Social Sciences--Health Professions                    24
12      Business, Management and Accounting-Economics,         23
        Econometrics and Finance
13      Social Sciences--Nursing                               21
14      Social Sciences--Economics, Econometrics and           21
        Finance
15      Medicine--Nursing                                      20
16      Computer Science-Decision Sciences                     19
17      Social Sciences--Chemistry                             16
18      Computer Science-Business, Management and              14
        Accounting
19      Social Sciences--Decision Sciences                     12
20      Social Sciences--Chemical Engineering                  11

Figure 2. Subject Area Wise Distribution of IL Publications

Subject Area

Veterinary                                     1
Physics and Astronomy                          3
Materials Science                              5
Energy                                         5
Dentistry                                      7
Pharmacology, Toxicology and ...               8
Neuroscience                                   8
Chemical Engineering                          10
Earth and Planetary Sciences                  11
Environmental Science                         12
Multidisciplinary                             13
Agricultural and Biological Sciences          15
Biochemistry, Genetics and Molecular ...      24
Chemistry                                     26
Economics, Econometrics and Finance           30
Decision Sciences                             38
Mathematics                                   53
Health Professions                            59
Nursing                                       65
Psychology                                    94
Business, Management and Accounting          148
Medicine                                     238
Engineering                                  242
Arts and Humanities                          299
Computer Science                            1042
Social Sciences                             2917

Please Note: Illustration(s) are not available due to copyright restrictions.