Web Impact Factor and Link Analysis of Indian Council of Agricultural Research (ICAR) Organizations

1. Introduction

In addition to user studies, there have been attempts to extract new kinds of information from the Web: examining, for example, the relationship between areas of the Web by counting the number of hyperlinks between them (Ingwersen, 1998). These kinds of studies, called “webometrics,” have grown out of bibliometric analyses of the citations in published journal articles (Borgman et al., 2002). Link analysis, like citation analysis in bibliometrics, has emerged as a research area of webometrics in recent years (Chu et al., 2005). There are different ways of calculating Web Impact Factors (WIFs), which use different definitions of the links involved (Kretschmer et al., 2008). Thelwall et al. (2005) classify three types of links depending on where links originate that are: inlinks, outlinks and self links. Most studies give two values of the WIF based on the number of inlinks and self links, which are sometimes combined into an overall WIF. Due to the limitations of existing data sources, Thelwall & Wilkinson (2003) used their own crawler for data gathering when comparing UK universities.

The Indian Council of Agricultural Research (ICAR) is an autonomous organisation under the Department of Agricultural Research and Education (DARE), Ministry of Agriculture and Farmers Welfare, Government of India. The vast network of ICAR includes Institutes, Bureaux, National Research Centres & Project Directorates. The present article examines Indian Council of Agricultural Research (ICAR) Organisations through a webometric study. The paper studies the link relationship and Alternative Document Model (ADM) count summary among organisations through various webometric indicators like simple Web Impact Factor (WIF), Self Link Web Impact Factor (SLWIF), External Link Web Impact Factor (ELWIF) and In-link Web Impact Factor (ILWIF).

2. Review of Literature

Based on web links or download numbers (Webometric) new evaluation methods have emerged as alternatives to the traditional citation-based metrics (Basili et al., 2016). Peker et al. (2016) statistically explores the relationship between web usability and web presence of the Turkish universities. The findings of the study revealed that Universities can estimate their web usability levels by investigating their web presence rankings and, can also raise their rankings in Webometric ranking system. Using the bibliometrics method, Sun et al. (2016) attempted to provide a comprehensive picture of national innovation studies based on data derived from the Web of Knowledge. The results were useful for understanding and promoting the field of national innovation. Chakravarty et al. (2015) calculated web impact factor (WIF) and R-WIF (Revised WIF) of top ten library websites of HEIs (Higher Educational Institutes) of India and further correlated both the formulas with Spearman's Rank Correlation. It was found that WIF and R-WIF are correlated and associated which depicts that there is very less difference between the two ranking methods. Noroozi et al. (2014) investigated the link and networks of Iranian research institute websites using webometrics and the link analysis method. The network diagram showed the mutual link strength and existing pattern among the set of research institute websites in Iran. Shukla et al. (2012) analyzed web presence of Indian State Universities (173) on the World Wide Web (WWW) and also found ways to get high web links that further help to improve presence on Web. The data was collected from Yahoo Site Explorer and Google Scholar. WISER ranking method was applied to assess the visibility and connectivity of universities on the Web. A WebCrawler Socscibot 4 was used to examine the pattern of link visibility and to create ADM Count Summary. The study showed that some state universities have more visibility than others. Thomas et al. (2000), Yazdi et al. (2013) described a link analysis of websites associated with departments of librarianship and information science (LIS).

3. Research Design and Methodology

3.3 Methodology

The Indian Council of Agricultural Research comprises a total of 100 different organizations: 4 Deemed Universities, 60 Institutions, 15 National Research Centers, 6 National Bureaux and 15 Directorates. It is clear from Table 1 that 92 orgnaisations have their own websites and rest of the organisational websites are not available or non-fuctional as of August 2015 to September 2015.

Table 1.

Sample Size

In addition to data extraction from web sites for webometric purposes (e.g. link analysis, ranking of Web sites, etc.), LexiURL searcher presents information on the arrangement of links among different web sites (Taram et al., 2015). In exploring hyper-linking behaviour of the web and retrieving relevant information, search engines and web crawlers play a predominant role as data sources (Jalal et al., 2015). Web search engines, and Google in particular, have created a generation of searchers who favor simple search engines available on the open free web (Jan Brophy et al., 2005). For this study data were retrieved using Google Search Engine and a personal Web Crawler Sociobiot 4.0 Version, since it is widely used and tested by many webomatricians for their studies in academic institutions.

Knowledge maps are tools that help visualize information. If bibliographical data are taken as the basis for network, Pajek become a simple means of getting to the crux of highly specific areas. (Garcia et al., 2015; Ruas et al., 2014; Cantos et al., 2014; Nagarkar et al., 2015; Kozak et al., 2015). The data are taken from a series of online snapshot searches over a single month (August 2015 to September 2015) performed on the Google by keeping various search conditions constant. Figure 1 denotes webometric query syntax.

Fig. 1.

Webometric Query Syntax

Web page classification (Onan et al., 2016) is the process of assigning a web page to a particular predefined category based on labelled data. It serves for several other web mining tasks, such as focused web crawling, web link analysis and contextual advertising. The following Figure 2 explains webometric query syntax and results.

Fig. 2.

Webometric query syntax supported by Google with results

4. Data Analysis and Interpretation

Numerous studies of Webometrics (Babu et al., 2010; Maharana et al., 2012; Vijayakumar et al., 2012; Jeyshankar et al., 2009) concerned measuring aspects of the web: websites, web pages, parts of web pages, words in web pages, etc. Link analysis is highly effective in detecting relationships between different institutions, relationships that are stronger the greater in their geographical proximity (Ontolba et al., 2016). Eight out of 100 ICAR organisations were excluded from the study due to server problems during the study period or non-availability of websites. Therefore, 92 organisationsal websites were considered. Table 2 shows the acronyms and explanations used in this article for calculating web impact factor.

Table 2.

Acronyms and explanations used in study for web pages

Table 3 shows the distribution of total number of web pages, link, self-link, external link and in-link web pages. It is clear from the table that ICAR-Institutions ranked first with 5,84,308 total web pages; 6,99,481 total links; 4,69,627.5 total self links; 5,35,923.5 total external links and 4,13,404.5 total in-links. ICAR-National Research Centres with 1,30,012 total web pages and 2,19,365 total links are in second postiton. ICAR-Deemed Universities holds third position in having 1,75,900 total self-link; 1,81,080 external links and 1,32,690 in-links. Project Directorates and National Beuroux are in fourth and fifth position with respect to distribution of web pages and links of all aspects. The WIF is useful in clarifying the significance of inlink (or total link) frequencies. However, the greater the number of link pages to a web site, the greater the WIF will be.

Table 3.

Distribution of Total Number of Web pages, Link, Self-Link, External, In-Link Web Pages

4.1 Alternative Document Model (ADM)

Webometrics deals with the application of infometric and other quantitative techniques for the analysis of Web documents (Jalal et al., 2009). There is a need for collecting data not only through commerical search engines but also academic web crawlers to overcome any bias. The advantage of an academic crawler is that it is possible to cover an individual website comprehensively within specified parameters. It is not possible for web crawlers to cover large web areas for which search engines are most appropriate. With a great deal of analysis for the data collected from search engines, Young et al. (2009) found the efficacy of the ADM approach in evaluating the metric data containing extreme outliers. Thelwall suggested an Alternative Document Model (ADM) to collect the link data for universities. The four parts of Alternative Document Model are reflected in Figure 3. The ADM count summary for ICAR organisations given in Annexure 1.

Fig. 3.

Four parts of the Alternative Document Model (ADM)

4.2 Link Topology for ICAR-Deemed Univeristies

Some of the ICAR Institutes have acquired the status of ‘Deemed University’ because of their achievements. It is obvious from Figure 4 that websites of Deemed universities are not well connected with that of the Main Institution. For example, ICAR, New Delhi posess 64 page out-links, 2 Directory links, 2 Domain out-links and 1 site out-link. It is surprising to note that National Dairy Institute, Karnal and Central Institute on Fisheries Education, Mumbai do not have any weblinks whatsoever.

Fig. 4.

Link Topology for ICAR-Deemed Universities

4.3 Link Topology for ICAR-Institutions

ICAR Institutions are established as Agriculture is a major sector of the Indian economy. They contribute greatly to GDP and provide more than 50% of employment. ICAR institutes are connected through Agricultural Research Information System (ARIS), a WAN with other ICAR institutions like universities, zonal agricultural stations, project directorates and others. These organizations collaborate in training and education for manpower and development. Figure 5 shows that ICAR-Indian Agricultural Statistics Research Institute, New Delhi have more number of weblinks than any other ICAR-Institutions. IASRI, Delhi has 44 page in-links, 37 directory in-links, 32 domian in-links, 17 site in-links, 1 page out-link, 1 directory out link, 1 domain out-link and 1 site out-link respectively. It should be noted that the following institutions have remarkable number of weblinks: Central Arid Zone Research Institute, Jodhpur; Central Research Institute of Dryland Agriculture, Hyderabad; and Indian Institute of Soil Sciences, Bhopal. The Figure clearly reflects that most of the institutes have inter relationship with ICAR, New Delhi, and ICAR-Indian Agricultural Statistics Research Institute, New Delhi also possess inter-relationship with ICAR-institutes such as Central Potato Research Institute, Shimla; Central Research Institute for Jute; Allied Fibres, Barrackpore; Indian Institute of Water Management, Bhubaneshwar; and Indian Institute of Horticultural Research, Bengaluru.

Fig. 5.

Link Topology for ICAR- Institutions

4.4 Link Topology for ICAR-National Research Centres

ICAR-National research centers is mandated to provide a research base to improve the productivity of important agri-horticulture, livestock and fisheries, poultry research as well as development activities in cotton technology, techno-economically viable and sustainable culture system for finfish and shellfish in brakishwater and so on. Certain regional research centers and stations were also merged to widen their scope towards agriculture development. While some of the older institutes existed as separate entities, some have been initiated by ICAR itself. Those agriculture research institutes which worked independently came under the governance of ICAR due to their experienced knowledge base. Figure 6 denotes Link topology formed among the ICAR-National Research Centers. Most of the National Reserch Centres have web links. National Research Centres for Banana, Trichy has 12 pages out-links while ICAR-National Research Centre for Citrus, Nagpur and National Research Centre on Camel, Bikaner each have 15 page out-links.

Fig. 6.

Link topology formed among the ICAR-National Research Centers

4.5 Link Topology for ICAR-National Bureaux

Realizing the unique significance of agricultural and animal resources and their potential utilization at global level, a need was felt for an organization which could undertake the responsibility of evaluating, certifying and conserving the country’s rich and varied resources. Thus, the establishment of ICAR-National Bureaux from sustained efforts made by the leading researchers in India over the years. The Bureaux has traveled a long journey in striving for excellence in innovative research to identify the uniqueness and genetic potential of the country’s vastly distributed livestock biodiversity and its sustainable development. Among the major achievements to its credit are the phenotypic and genetic characterization of the majority (> 90%) of the registered breeds of cattle, buffalo, sheep, goat, equines, camel and poultry. Figure 7 reflects that there prevails a good relationship among National Bureaux under ICAR. It is interesting to note that National Bureau of Agriculturally Important Micro-organisms, Mau, Uttar Pradesh have web link distributions with Fish Genetic Resources, Lucknow, National Bureau of Plant Genetics Resources, New Delhi and National Bureau of Animal Genetic Resources, Karnal.

Fig. 7.

ICAR-National Bureaux

4.6 Link Topology for ICAR-Project Directorates

The basic mandates of Project Directorates are strategic and adaptive research on agricultural productivity and quality. They provide access to information, knowledge and genetic material to develop improved technology and enhance agricultural production. Figure 8 shows the visualized network of ICAR-Directories Project. From the figure, it could be understood there exists a progressive network between ICAR and other directorates. Only the Directorate of Rice Research, Hyderabad and ICAR-Directorate of Seed Research, Mau have a web link relationship.

Fig. 8.

ICAR-Directories project

5. Major findings and Suggestions

In the present research system, the role of ICAR at the national level in aiding, promoting and coordinating research and education activities across the country is of significant importance. Since independence, there has been a substantial growth in the Indian agricultural research system. ICAR is the chief public body at the national level for directing and endorsing agricultural research and education in the country. Likewise, State Agricultural Universities are responsible for doing the same at the state level. In this study, the Web Impact Factor (WIF) for each ICAR organisation has been calculated in four levels. Simple Web Impact Factor (SWIF) considering all the link pages, Self-link Web Impact Factor (SWIF) considering only self link pages, External-link Web Impact Factor (ELWIF) considering only external link pages and In-link Web Impact Factor (ILWIF) considering only in-link pages. Since it is the true refelection of the degree of impact of the domain spaces on the WWW, Web Imapct Factors for each ICAR Organisations are caculated based on formula given in Table 2. The report revealed that National Beuraux occupied first place with simple web Impact factor of 2.09. Deemed Universities procured first place with self-link web impact factor of 1.74; external-link web impact factor of 1.45 and in-link web impact factor of 1.06. National Research Centres are ranked second with respect to SWIF of 1.69; SLWIF of 0.91 and second, third rank concerning to ELWIF of 0.91 and ILWIF of 0.71. ICAR-Institutions occupied fourth place with respect to SWIF of 1.20; SLWIF of 0.08 and ELWIF of 0.92. Project directorates were in fifth rank concerning to SLWIF of 0.43 and ELWIF of 0.46

The study also focused on .link analysis which is a recognized focus within webometrics. It normally uses counts of links between sets of web sites or to sets of web sites. These link counts are derived from web crawlers or commercial search engines with the latter being the only alternative for some investigations (Thelwall, 2011). The results clearly show that almost all National Bureaux have link with ICAR-New Delhi. ICAR-National Bureaux of Plant Genetics Resources, New Delhi has more in-links and out-links compared to the rest of the National Bureaux. It is important to notice that ICAR-National Bureau of Animal Genetic Resources, Karnal does not have a direct link with ICAR, New Delhi; instead they have a link with National Bureau of Agriculturally Important Micro-organisms, Mau, Uttar Pradesh. The study found that ICAR-Directorate of Rice Research, Hyderabad has more web links, followed by Directorate of Mushroom Research, Solan and ICAR-Directorate of Medicinal and Aromatic Plants Research, Anand. The Radar plot in figure 9 shows distribution of overall links with ICAR-Organization.

Fig. 9.

Distribution of Overall link with ICAR Organizations

It could be understood from the figure that ICAR-Institutions hold first position with respect to 68 pages in-link, 45 directory in-links, and 33 domain in-links. National Research Centres are ranked second concerning to 67 page in-links, 23 Directory in-link, 11 Domain in-links, 10 site in-links and 27 page out links, and they secure first place related to 22 directory out links, 15 domain out link and 15 out links. National Bureaux holds third position pertaining to 15 Directory in-links, 8 Directory out links, 3 domains out links and 3 sites out links; they are placed fourth with respect to 38 page in-links, 5 Domain in-links, 4 site in-links and they secure first position with 33 pages out links among ICAR-Organizations.

6. Conclusion

One of the original objectives of ICAR was to undertake aid, promote, and coordinate agricultural education in the country. At present, ICAR plays a central role at the national level and it aids, promotes, and coordinates research and education activities throughout the country. The research and education responsibilities at the state level rest with the State Agricultural Universities. Webometric analysis offers an evaluation measurement that is lacking in bibliometrics when an institution is the analytical unit; however Webometric research must be conducted with caution, because both the data source (i.e., Web-based data) and data collection instruments (i.e., Web search engines) have obvious deficiencies (Chu et al., 2001). This paper explored the application of various forms of web impact factors as a method of ranking ICAR Organizations. There is scope for future Webometric research in this area. It would be useful to carry out a more comprehensive study comparing more ICAR organizations and comparing web with conventional publication output and indicators of academic and technological development.

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