Bibliometrics: Application Opportunities and Limitations

Abstract

With the advent of information and communication technology, research is increasingly being published; hence, keeping abreast with current research in any field is challenging. Bibliometric analysis has the capabilities to deal with this issue, since it can be used as a rigorous method of accessing and understanding massive scientific data that is continuously created. Using various indicators, bibliometric analysis enables the impact of scholarly publications and research out of institutions and countries to be assessed. Through the assessment of dynamics in research, bibliometrics provides opportunities for managing massive research data and knowledge and identification of gaps. Despite these advantages, bibliometric analysis has limitations; hence, to successfully apply bibliometric analysis, one has to be aware of both opportunities and limitations. This book chapter seeks to enable bibliometric analysis users to make informed, balanced decisions between the opportunities bibliometric analysis provides and the accompanying limitations. Information that will assist bibliometric analysis will be generated in this chapter through analysis of bibliometric literature.

1. Introduction

First, defined by [1], bibliometric analysis is useful in identifying essential information for various purposes like prospective research opportunities. Based on citations, biliometric analysis enables the identification and analysis of the performance of research articles, journals, institutions and countries. Bibliometric analysis provides a means to give direction in the development of research projects [2]. The publication pattern in the world has been impacted positively by the advancements in information and communication technology (ICT). The ease with which people acquire and share information rapidly and efficiently has been enhanced through the extensive availability of digital media [3]. ICT has increased the range and depth of any topic, the number of scholars working on any topic and the number of publications that describe findings in the same field [4]. Competitiveness has led many countries to increasingly invest in scientific and technological development, which is essential for a sustainable economy [5]. Among other things, this development has led to the publication of many research articles daily, which are available in international databases for dissemination as research output from researchers in various universities and countries [6].

In this context, bibliometric analysis is an important way of measuring, monitoring and studying research outputs. Biliometric analysis enables mapping and expansion of knowledge in a particular area of research, as well as showing connections between publications, authors and institutions [7, 8]. As a tool for evaluation bibliometric analysis is used to justify decisions on research policies, funds, job offers, promotions and support for research projects [9]. With knowledge continuously evolving, bibliometric analysis is crucial in revealing research gaps [2]. Continuously increasing research publications in any field are progressively making it challenging for researchers to keep abreast with knowledge that is being created. As [10] stated, bibliometric analysis has the potential to mitigate this challenge. As the research landscape continues to expand rapidly, it is important to apply efficient methods for identifying research opportunities. Within interdisciplinary research framework, bibliometric analysis proves to be able to discover promising research areas. Bibliometric analysis is important in locating research opportunities, as well as enabling productivity in science to be understood by evaluating parameters like the number of studies, citations, and h-index [11]. Bibliometric analysis assists in exploring literature for relationships between scientific culture and social science issues in publications indexed by Scopus Database [12].

Due to its rigour in gaining access to and making sense of massive data, bibliometric analysis is widely used [13]. The rigour of bibliometric analysis is hinged on its use of quantitative and statistical approaches to analyse written material and explain behaviours [1]. Dissemination and impact of scholarly publications can be assessed using a variety of indicators and measures through bibliometric analysis [14]. Productivity, quality of research within a field or discipline, influence of specific publications and ability to identify publishing and citation trends can be determined by bibliometric analysis [15]. It is also important to note that bibliometic analysis promotes understanding of the structure and dynamics of study topics, which helps to identify developments in research areas, key players and knowledge gaps, hence areas for further research [10].

Methodological foundations of bibliometrics are quantitative production, growth, maturation and consumption of scientific publications. In this sense, the term bibliometrics was originally coined by [1], replacing statistical bibliographies. Currently, massive amount of data published in academic journals, books, patents, proceedings, etc., are organised and stored in bibliometric databases. These platforms, that is, citations, keywords, titles, journals, authors, institutions, etc., provide valuable sources for performing evaluation of research output using bibliometric techniques [16]. Bibliometric analysis has become important for assessing a researcher’s output [17], collaboration between institutions [18], impact of scientific investment in national R&D productivity [19]. Indicators that are used in bibliometrics analysis include number of publications, number of citations, number of non-cited publications, research field classification and normalised citations. Scientific maps which represent relationships among different actors like authors, institutions and countries, can enhance bibliometrics analysis. Small (1999) in [20] defines a scientific map as a spatial representation of how disciplines, fields, individual papers of authors are related to each other by their relative locations. Having introduced the chapter through preceding paragraphs, the next paragraph explains the methodology used to develop this chapter.

Any knowledge has opportunities as well as limitations it offers to users. In this context, this book chapter seeks to enable bibliometric analysis users to make informed, balanced decisions between the opportunities bibliometric analysis provides and the accompanying limitations. The methodology used to develop this chapter involved the critical selection of publications, mostly from journals. Analysis of selected literature was done with the view of establishing themes that were logically aligned with the purpose and title of the book chapter. Analysis done under these themes subsequently led to the conclusion that highlights key issues in bibliometric analysis.

2. Bibliometrics databases and software

Gathering and assessing bibliometric data is possible through the availability of various databases and software applications. Bibliometric databases are discussed in Section 2.1 and bibliometric software in Section 2.2.

2.1 Biliometric databases

2.1.1 Web of Science and Scopus

When a researcher has defined the research area, the next crucial step is selecting robust databases from which to source data for bibliometric analysis. Currently two major databases available internationally are provided by Thompson Reuters Scientific as Web of Science (WoS) (www.webofknowledge.com) and Scopus (www.scopus.com). Various academic journals [10], conference proceedings and books are indexed on these databases, hence many scholars locate relevant publications as well as evaluating their impact and citation trends [21]. The Thompson Reuters Scientific database (WoS) covers 9000 of the most important journal titles selected mostly on the basis of their citation impact [22]. Web of Science (WoS) website provides access through subscription to multiple databases and citation data for 256 disciplines (science, social science, arts, humanities). The original producer of WoS was the Institute for Scientific Information (ISI). Later the intellectual property of WoS was given to Thomson Reuters, and currently maintenance is the responsibility of Clarivate Analytics. Various formats such as full-text articles, reviews, editorials, chronologies, abstracts, proceedings (journals and book-based) and technical papers are covered by WoS [20]. This (WoS) database can be used to analyse the occurrence of publications by year, publication by source information and authors, journals, countries, institutions, thematic maps, and current trends in a particular research field [10]. Scopus website offers access to databases and citation data on life sciences, social sciences, physical sciences and health sciences. It covers 15,400 journal titles across natural and social sciences, art and literature [21]. Elsevier provides through subscription, access to Scopus, for three types of biliometic analysis data sources namely, book series, journals and trade journals [20]. Bibliometric analysis can be used to explore research or publication trends indexed by Scopus database. For instance, the authors [22] posit that relevant literature between scientific literacy and socio-scientific issues can be explored through bibliometric analysis. Scopus can also be used to determine the number of publications, citations and h-indexes for researchers [11] such as extensive multidisciplinary databases Scopus and WoS are sources of publications. These databases provide data that is used to compare the performance of research articles according to each platform and then corroborate, complement or refute the results [2].

Integration of research data provided by these platforms makes it possible to obtain robust results from bibliometric analysis. Using search strategies which reflect the research topic, study objectives and the limits of the research field, high-quality data mining is made possible. Specific terms to the research field, publication period, document type, language and area of knowledge are the main criteria used in bibliometric analysis. Before data analysis, articles that do not belong to the field of study should be eliminated from the search results [2]. As is common with administration journals, some publications do not use keywords, so the researcher needs to review titles and even abstracts in the case of inaccurate titles to identify terms or expressions that identify the main topics covered [23, 24]. Titles of articles are bibliometric data which expose the most cited articles through the number of citations received. Classification of articles according to the number of citations reveals those that are among the most researched literature. Generating a chart with the most cited articles helps to reveal the evolution of citations for articles over the years, hence clarifying articles which increased in importance in the scientific world [2].

2.1.2 Google Scholar and Microsoft Academic

While Scopus and WoS are the most popular databases, it is important to note that other databases like Google Scholar may be suitable for particular research fields or subjects. Google Scholar was launched in 2004 as a freely available website. Full text or metadata of scientific literature from peer-reviewed online academic journals, books, conference papers, theses, preprints, abstracts, technical reports, court opinions and patents are indexed on this website [20]. While there is an acknowledgement of Google Scholar's convenience, its extensiveness and precision have been questioned [10]. Previously known as Microsoft Academic Search, Microsoft Academic (MA) was relaunched in 2016. Currently, it has over 230 million publications, of which 88 million are journal articles.

2.2 Bibliometric software

Bibliometric software assists researchers in analyses of bibliometric data to identify research trends, collaboration networks and citation patterns. Some prevalent bibliometric software includes VOSviewer, ScientoPy, Bibliometrics and SciMAT. It is important for researchers to bear in mind that while strengths of bibliometric software are applauded, each software has weaknesses such that it is important to decide when it is appropriate to use each software. There is also Python package ScientoPy which provides many tools for bibliometric analysis which include data extraction, cleaning and visualisation. In addition, it can analyse citation networks, co-authorship networks and keyword co-occurrence [25]. An R package Bibliometrix provides a variety of bibliometric functions which include co-authorship analysis, citation analysis, and visualisation of bibliomentric networks [26]. Visualisation and scientific literature analysis in a longitudinal framework, implying consideration of changes in the research landscape, can be done using SciMAT, an open-source software tool. SciMAT has the strength of providing researchers with modules of all steps of science mapping workflow, involving data collection, pre-processing analysis and visualisation [27].

VOSviewer allows researchers to view bibliometric data in various formats like co-authorship networks, co-citation networks and bibliographic coupling networks [28]. VOSviewer is handy for analysing and visualising large bibliographic data sets and identifying trends and patterns in literature [29]. This software tool allows the construction and visualisation of bibliometric networks, with journals, researchers or individual publications as actors, based on co-citation, bibliometric coupling, or co-authorship relations [28]. VOSviewer software is also used to identify specific research areas by discipline from keyword co-occurrences of the citing articles. Visibility through referencing and author keywords is limited despite that bibliometric software tools are making a noteworthy impact and contribution to research. Therefore, there is a need to raise awareness and initiate discussions on the citing practices of software tools in scholarly publications [30]. Notably, each bibliometric analysis software has advantages and disadvantages; hence, users should select the appropriate software for a particular analysis.

3. Bibliometric analysis linked opportunities

Academic endeavours to create knowledge and understand the world are dynamic targets which continuously change and, hence difficult to attain. This continuously provides opportunities for doing research. Therefore as long as humans are on earth, research will continue indefinitely. Irrespective of the field, research requires a research plan and the establishment of connections to prior knowledge [31]. As a process, research leads to new insights, discoveries and innovations; hence, national development requires research of all kinds [32]. In order to keep abreast with advances in any field, respective researchers need to be aware of current research publications. This will ensure that their research is up-to-date with the latest developments and technologies [33], which may impact their work and enable them to adjust their research plans appropriately [34]. Bibliometric analysis is important because it makes opportunities available to researchers, funders, institutions and countries. Some of these opportunities are discussed below.

3.1 Effective use of resources

Duplications waste financial and material resources for both researchers and funders. Therefore, avoiding duplications in research by identifying promising research possibilities is important because effort and resources are appropriately used. This ensures that resources are effectively used and quality research is conducted [10]. Research gaps and promising study fields can be identified using bibliometric analysis by considering the number and distribution of research publications and themes. This way, research areas that have gaps are identified. Mapping appropriate information for a study through bibliometric analysis in the initial phase can ensure that relevant literature is considered for the construction of new research [2]. Such an approach avoids duplication of research projects, which ensures optimum use of resources and focus of effort on promising areas of fields of study.

3.2 Partners or collaborators identification

Partners or collaborators can be identified through bibliometric analysis [35]. Through analysing co-authorship networks and collaboration patterns, bibliometric analysis can reveal researchers working on similar topics or having complementary skills, which provides opportunities for interdisciplinary collaborations and partnerships. Chiroma et al. [36] note that bibliometric analysis has the potential to allow researchers to determine areas that need further development, as well as identify potential collaborators at author, institutional and country levels. This encourages research networking among individual researchers, institutions and countries.

3.3 Funding

Funders are increasingly requiring evidence that the research they support has the potential to impact society's innovations [37, 38]. If properly analysed, bibliometric indicators give a research project consistency [8]. There is a possibility of presenting objectives and methods of research work precisely and concisely by a researcher who develops a research project based on bibliometric analysis. Gaps to be filled by the intended research will be illustrated [2]. This gives potential funders confidence that the proposed research project will succeed; hence, they are willing to fund.

3.3.1 Funding and impact of research nexus

As an evaluation methodology, bibliometrics analysis applies quantitative analysis to measure patterns of scientific publication and citation, typically focussing on journal papers. Case study analysis, peer review, surveys and consultations may be used to assess the impact of research in various fields [21]. Evaluation and tracing of research trends and scientific quality output are performed by application of bibliometric analysis. As a strategic approach, funding agencies seek to evaluate the impact of the research they fund in order to ensure that the intended objectives are achieved. Bibliometric analysis helps funders to evaluate the research impact of higher education institutions and make informed decisions on funding [39, 40].

Inequality in funding research is widespread. One of the causes of this inequality is the bias of evaluation and funding mechanisms since some funders are more inclined to known research areas or researchers. Therefore, upcoming researchers can use bibliometric analysis to identify possible partners [41]. However, it is important to note that promising areas of research or researchers may lose funding for not being well known. To address this inequality in funding research, governments should create policies which promote increase in funding. In addition, assessment of project applications should be done carefully. Therefore, there is a need for fair evaluation criteria that focus on supporting innovative and risky research projects, avoiding preference for known researchers [42].

3.3.2 Funding acknowledgements

Funding is critical for research to be done [40]. There is no standard way of acknowledging funders by researchers, resulting in inconsistencies between journals and research fields. However, a reliable way of linking publications to funding schemes and funders can be achieved through funding acknowledgement (FA) data available on databases in Thomson Reuters’ Web of Science (WoS) [40]. One of the key limitations associated with use of FA data from the Thomson and Reuters database is that it began recently in in mid-2008 to index FA data, for only articles included in Science Citation Index. FA for the Social Science Citation Index (SSCI) became available in 2015. Another important limitation to the use of FA to link funding agencies and published articles is the exclusion by some researchers of FA [43]. In some cases, researchers may include FA even if the publication is not closely related to the funding received. Nevertheless, false positives are reduced through the use of FA data from WoS since it allows a more precise and direct linkage of funding agencies and published articles [40].

The use of citations in bibliometrics is a standard practice whose limitations are acknowledged. In order to inform decisions on who to fund based on research performance, there is a need for a credible way to do this. Therefore, when comparing the scientific impact of different publications or groups of publications, normalised citation counts are usually preferred to raw counts. The normalised citations are calculated by dividing the number of citations of that article by the average number of citations published in the same year in the same field.

3.4 Bibliometric analysis application in evaluation

Bibliometric analysis can be used to generate useful quantitative indicators of collaboration and measures of interdisciplinary research. Bibliometrics analysis is an approach for measuring research output anchored on the methodological reliability of bibliometric measures. If a paper has many authors, there is no clear way of distinguishing relative contributions made by each individual. In practice, citations on papers are attributed to all named authors during evaluations. In order to achieve high-quality bibliometric analysis, there is a need for a clear understanding of the strengths and limitations of each of these measures, as well as sensitivity to the contexts in which they are used [21].

Tied to review by experts, bibliometric analysis increases the objectivity of and confidence in evaluation. However, caution should be taken when using indicators derived from publication and citation data, since some fields publish faster than others and citation rates vary. This points to the need for citation counts to be carefully normalised to account for such variations by field. Usually, normalisation is done by reference to the relevant global average for the field and for the year of publication. Since citation counts grow over time, it is essential to account for growth by year [44].

3.4.1 Premise of citation assumptions used in evaluation

For evaluation purposes, an extensive range of measures of research performance have been developed in citation analysis. The development of measures for bibliometric analysis is underpinned by important assumptions, which are:

1. document citation suggests the use of the document by concerned authors;

2. merits like quality, significance or impact of the document are reflected by its citation;

3. best possible work is cited;

4. citing document is related to the cited document;

5. although field adjustments can be made to take account of the number of citations that a paper receives relative to others in the same field, all citations are considered equal [21].

3.5 H-index research output measurement

The h-index is an effective parameter in determining academic strength [11]. An indicator receiving a lot of attention for measuring the quality of researchers and organisations is the h-index, since it shows papers that are highly cited [45]. H-index can be used to determine the impact of papers. Data on publication can be obtained through bibliometric analysis from Web of Science, and most prolific countries or individual researchers can be established using paper productivity as a criterion [46]. A study by [46] established a strong positive correlation (r = 0.864) between the h-index and the number of papers published by the countries. H-index was developed for evaluating researchers, and it has been extended to include academic output and the widespread effects of publications by researchers or countries [47]. The h-index is also an effective parameter in determining academic strength [11].

A country’s overall scientific achievements in a specific field can be consistently estimated by the h-index, since it includes the total number of publications and citations. In other words, the h-index is designed to assess both the quality and quantity of scientific papers in a cumulative approach. Premised on this, Sezgin et al. [46] report a positive correlation between the quality and quantity in the field of special education of publications of countries. Deviation of positive correlation, especially the journal quartiles (Q), the level of international collaboration (IC%) and the percentage of open access papers (OA%) have a significant effect. The USA is the leading country in terms of both the number of published papers and the h-index. However, it is crucial to note that countries which make the most impact in terms of the widespread impact of the publications (h-index) are not those with the highest number of publications [46].

3.6 Ranking of institutions

Progressively bibliometric analysis is being integrated into methods of evaluation to assist R&D policymakers in making decisions. In countries like United States, United Kingdom and Australia, there is evidence of gradual shift in the past 10 years towards a model of university assessment and ranking using bibliometic measures. The Department of Health in England (Britain) has shown interest in using bibliometric analysis to assist in making decisions in R&D; hence, it has engaged RAND Europe’s expert in this [21].

3.7 Discovery of research opportunities/identifying gaps

3.7.1 Authors countries, institutions, articles and keywords analysis gap and research trends identification

A researcher can know the most referenced authors through analysis of the most cited authors. This analysis may indicate to the researcher opportunities for co-orientation partnerships and participation in international research groups. One way that can be used to identify gaps is analysing the most commonly used keywords in articles on a given topic. The high frequency of keywords in the portfolio of documents analysed in bibliometric analysis is the criterion for measuring the relevance of a particular topic. This way, it can be determined whether a topic has been sufficiently explored or gaps exist. Researchers should pay attention to keywords that were used previously in articles but no longer used with such frequency. This may be an indicator of the exhaustion of a theme in literature. VOSviewer software is appropriate for this analysis since it automatically counts the number of keywords that are occurring in selected articles [2]. The implication is that the researcher will not waste effort focussing on such areas for research. Similarly, funders will not fund research in such areas.

Reading research articles is a way of identifying gaps. Gaps which are explicit in the text of an article, usually in the conclusion section, can be easily identified. Also, difficulties faced in conducting a study can provide explicit gaps that may originate new research. If research with similar objectives is geographically limited, then the gap is in the application of the study in other regions, countries or continents. Reading is another way of identifying implicit gaps in text. In order to identify implicit gaps, the reader/researcher carefully analyses shortfalls which are implicit in the text. The reader’s experience with the topic is important for easy identification of such gaps [2].

3.7.2 Grouping, timeline, and analysis of interactions: gap and research trends identification

Timeline analysis, grouping topics analysis, and searching for similarities between various groups can be done with bibliometric analysis to identify gaps and trends in research. Mastery in the state of the art of the field being studied is required when topics are grouped into sub-areas. Analyses of most cited authors and articles, countries and research centres are important because, through them, rich information is extracted that helps the perception of similarities, formation of groups and identification of research trends to be made. Content analysis is the appropriate technique used to make groups, as the researcher identifies the most recurring topics. Visualisation of analysis can be facilitated with a chart that shows the frequency of occurrence of particular elements in literature, hence revealing the most recurrent topics, which are then used to form groups.

3.7.3 Citation analysis for gap identification

Bibliometic analysis enables researchers to identify impactful publications in specific fields. Analysis of citation patterns can reveal the most highly cited publications, giving valuable insights into the development of a research field over time. Observed trends can inform the development of new research projects, guide researchers on potential collaborators, and inform policy decisions in various organisations. Bibliometric analysis can reveal the most highly cited publications, hence identifying the most influential authors in a study field. Also, bibliometric analysis enables researchers to understand the current state of a research field and identify the most pressing issues that need to be addressed.

Identifying the most highly cited publications in a study field assists in the identification of gaps for further study, as well as providing insights into potential collaborations or funding opportunities. By quantitatively analysing publication and citation data [17], bibliometric analysis can be utilised to discover research opportunities in various research fields [48, 49]. Through analysis of publication and citation data, researchers gain insights into the most trending research topics in a particular discipline [50]. This helps researchers to highlight research gaps and possibilities to inform future research trajectories. Therefore, bibliometric analysis is a tool that can initiate impactful original research in addressing crucial societal issues, as well as widen frontiers of knowledge in various areas.

4. Bibliometric analysis limitations

4.1 Citation data bias

Attending to the limitations of bibliometric analysis can increase its usefulness. One such limitation is bias in citation data. Bias can be in favour of high-impact articles or authors from prestigious institutions at the expense of upcoming ones. To mitigate these biases, one can use altmetrics or complex citation analysis algorithms that account for quality and relevance of the citations [51].

4.2 Exclusion of qualitative data

Bibliometric analysis provides quantitative data at the expense of qualitative components of research. Qualitative factors like the research’s quality or its impact on society are not catered for in the provision of data by bibliometric analysis. To address qualitative factors, it is necessary to include qualitative criteria like peer review, societal influence and ethical considerations. Through peer review, rigour of scientific discoveries and validity is ensured.

4.3 Interdisciplinary nature of research

Research is interdisciplinary in nature, yet bibliometric analysis is discipline-specific and this can impede interdisciplinary research. Against this background, efforts should be made to promote interdisciplinary bibliometric analysis by introducing cross-disciplinary indicators that capture the diversity of research collaborations.

4.4 Limitations to use of bibliometrics

• Different methodologies for collecting and reporting bibliometric measures use citation-tracking databases. This may produce significant limitations to some disciplines when research publications from various fields of study are indexed.

• Not every type of publication can be indexed by a citation-tracking database, and comprehensive coverage of research publications is not possible. This limited coverage is reflected in the research analytic tools (such as InCites and SciVal) that draw on data from citation-tracking databases. Proprietary citation-tracking databases (such as Web of Science and Scopus) index different collections defined by the publications their commercial enterprises hold. Google Scholar, while not defined by proprietary collections, is limited by search conventions that can include non-scholarly works.

• Academic discipline outputs include patents, papers in conference proceedings, produced systems developed and widely used, data sets or hardware and software artefacts, policy papers, white papers and reports produced for government and other public organisations, books or works produced and exhibitions. However, not all of these outputs are indexed equally well by citation-tracking databases.

• There is poor coverage by citation-tracking databases of research that is not published in English. Therefore, the field-specific context for research outputs like the extent and type of some research collaborations cannot be provided.

• Across disciplines and fields, the practice of attributing citations and collecting citation data differs. Citations in some fields accrue within a few years after the publication of work, while in some fields, it takes many years. Differences in citation practices carry over into every bibliometric measure that uses citations as part of calculating the metric, including the h-index.

• Gender bias is evident in citation practices, thereby underestimating contributions made by women researchers. This should be considered when conducting bibliometric analysis.

• Meaningful comparisons cannot be made for bibliometric measures taken at different times. Citations, as a key research bibliometric measure, accrue with time after publication. Also, the time required to understand the impact of a paper using citations differs by discipline. Citation databases change their methodology and journal coverage over time.

• Changes which arise due to use of bibliometric measures include how researchers choose to publish, increase in opportunities for enhanced coverage in citation-tracking databases, and what they choose to research. It may provide opportunities and incentives to manipulate metrics. When using bibliometric tools, cross-disciplinary differences may be misinterpreted as cross-disciplinary differences in research activity or impact itself [52].

Also it is important to note that while absolute numbers/rankings are easy to understand, population-weighted figures allow smaller countries not to be drowned out of analysis by bigger countries [53]. Bibliometric analysis application is not universal or the same across disciplines; hence, context needs to be considered.

5. Discussion

Bibliometric analysis allows knowledge gaps to be identified and ideas for areas of inquiry to be developed. Due to continuous change in the research landscape, experts in any discipline must keep abreast with the most recent research output in their field [30, 33]. Identification of new areas of study ensures discoveries are still relevant. Policymakers and funding agencies allocate resources to promising areas, and they put effort wisely to sustain research. Also, to benefit society through research and innovation, bibliometric analysis identifies areas where more should be done. An important application of bibliometric analysis is the identification of the most influential journals and authors in an area of research. This information is useful in designing future studies, formulating policy, and selecting research partners [54]. Comprehension of current research status, identification of research gaps, and new research fields are possible through bibliometric analysis [55].

Most cited works and authors can be identified by bibliometric analysis, which may show how a particular field evolved or is evolving. Analysis of co-authorship networks and collaboration patterns in bibliometric databases can show scholars working on similar issues or complementary talent, hence promoting multidisciplinary collaborations and partnerships [34]. Quality of data and accessibility in bibliometric analysis could be improved by adopting standardised metrics and instituting data-sharing standards. Such improvements can make bibliometric analysis a very robust tool for assessing the quality of scholarly work [10].

6. Conclusion

Bibliometric analysis offers opportunities to do research, avoiding duplications by identifying promising research possibilities. This ensures that financial and material resources are not wasted for both researchers and funders. Through analysing co-authorship networks and collaboration patterns, bibliometric analysis can reveal researchers working on similar topics or having complementary skills, which provides opportunities for interdisciplinary collaborations and partnerships. Researchers use bibliometric software to analyse bibliometric data so that they can identify research trends, collaboration networks and citation patterns. Some prevalent bibliometric software include VOSviewer, ScientoPy, Bibliometrix and SciMAT. It is important for researchers to bear in mind that while the strengths of bibliometric software are applauded, each software has weaknesses, such that it is important to decide when it is appropriate to use each software.

Although bibliometric analysis has application opportunities, it also has its caveats which should be taken into account for effective application. For instance, it cannot capture research quality, so the accuracy and breadth of bibliometric analysis depend heavily on data sources. It is important to note that bibliometric analysis is not a substitution for content analysis or other methods of gaining insight into a research field. However, notwithstanding these limitations, bibliometric analysis remains an effective tool for discovering new areas of enquiry and making informed decisions by researchers on where to focus efforts.