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Given the magnitude of the literature, a researcher must be selective of research papers and publications in general. In other words, only papers that meet strict standards of academic integrity and adhere to reliable and credible sources should be referenced. The purpose of this paper is to approach this issue from the prism of scientometrics according to the following research questions: Is it necessary to judge the quality of scientific production? How do we evaluate scientific production? What are the tools to be used in evaluation?

This paper presents a comparative study of scientometric evaluation practices and tools. A systematic literature review is conducted based on articles published in the field of scientometrics between 1951 and 2022. To analyze data, the authors performed three different aspects of analysis: usage analysis based on classification and comparison between the different scientific evaluation practices, type and level analysis based on classifying different scientometric indicators according to their types and application levels and similarity analysis based on studying the correlation between different quantitative metrics to identify similarity between them.

This comparative study leads to classify different scientific evaluation practices into externalist and internalist approaches. The authors categorized the different quantitative metrics according to their types (impact, production and composite indicators), their levels of application (micro, meso and macro) and their use (internalist and externalist). Moreover, the similarity analysis has revealed a high correlation between several scientometric indicators such as author h-index, author publications, citations and journal citations.

The interest in this study lies deeply in identifying the strengths and weaknesses of research groups and guides their actions. This evaluation contributes to the advancement of scientific research and to the motivation of researchers. Moreover, this paper can be applied as a complete in-depth guide to help new researchers select appropriate measurements to evaluate scientific production. The selection of evaluation measures is made according to their types, usage and levels of application. Furthermore, our analysis shows the similarity between the different indicators which can limit the overuse of similar measures.

Assessing the research performance of researchers offers inducement toward excellence in research. This study aims to analyze the research productivity of the most prolific authors of Pakistan considering their trends toward publications, citations and collaboration.

Top 100 authors from the top 10 Pakistani universities from Web of Science over the 10 years with the rigorous data cleaning process were selected. Scientometric analysis techniques were carried out to evaluate the research profile of these authors.

The findings revealed that majority of the productive authors were male working in the position of Professor in the physical sciences area. The publications and citations gradually increase with time. They preferred to collaborate for their publications, while first authorship publications were found less in number. Moreover, the propensity to collaborate at the international level increases double-fold from the first five years to the next five years period. In addition, the position of the authors was explored among different performance metrics. The finding exhibits variation in the ranking of authors among them. The impact of numbers of authors, funding status, publication of articles, presence of collaboration and international collaboration on the dependent variable and citation count was insignificant. However, the publication of review papers has a significant impact on the citation counts.

Findings have significant implications for policymakers to make maximum opportunities for researchers to strengthen linkages for collaboration and increase the funding prospects.

Studies on this topic are scarce, and therefore, this study provides useful recommendations to researchers and institutes to improve research productivity.

The purpose of this study is to gain insight into how citations are distributed and concentrated in the introduction, methods, discussion, results and other sections of journal articles to determine which section has received the most citations and whether the citation concentration score affects how articles rank.

The present study uses scite.ai and the Dimensions database to emphasize the significance of including multiple in-text citations in evaluating the impact and quality of journal publications. The study has two approaches: paper-based and author-based.

The study provides empirical insights into how variations in ranking are observed when citation concentration is considered in the evaluation process. It also suggests that in-text citations be used as an evaluation criterion or aspect for assessing the impact and quality of journals, publications and authors.

This study underscores the importance of considering citation concentration when evaluating journal articles. To assess highly cited articles, it suggests using the CC-index method, which is based on scite.ai.

The purpose of this paper is to determine the relationship between the access mode of research articles [Open Access (OA) and Toll-Access (TA)] and their subsequent citation counts in Biological and Physical Sciences in three Impact factor zones (High, Medium and Low).

Three subjects each from Biological Sciences (Biochemistry, Cell Biology and Genetics) and Physical Sciences (Astronomy, Oceanography and Optics) were selected for the study. A comprehensive list of journals (TA and OA) in select subjects of Biological and Physical Sciences was prepared by consulting Journal Citation Report’s Master Journal List (for the compilation of both Open Access and Toll Access journal list) and Directory of Open Access Journals (for the compilation of Open Access journal list). For each journal, essential details like content language, format, year of publication, access mode (Open Access or Toll Access), etc. were obtained from Ulrich’s Periodical Directory. Web of Science (WoS) was used as citations indexing tool in this study. The data set was run on the WoS to collect the citation data.

The results of the study indicate that open mode of access is not a prerequisite for higher citation boost as in the majority of the cases in this study, TA articles have garnered a greater number of citations as compared to open access articles in different Impact factor zones in Biological and Physical Sciences.

A novel approach has been adopted to understand and compare the research impact of open access (OA) and toll access (TA) journal articles in the field of Biological and Physical Sciences at three Impact factor zone levels to reveal the citation metrics encompassing three parameters, i.e. citedness, average citation count and year wise distribution of citations in select subjects of Biological and Physical Sciences.

The peer review history for this article is available at: https://publons.com/publon/[DOI]/10.1108/OIR-01-2021-0029

This study aims to conduct a bibliometric analysis on knowledge management from journals in the Scopus database between 1988 and 2021. The paper covered the past three decades of publications and carried out performance analysis and science mapping analysis of articles.

The study uses bibliometrics, performance analysis and science mapping analysis of 1,016 articles extracted from the Scopus database. The study examined the scientific productivity of articles, productive authors, citable documents, most relevant institutions, cited countries, co-occurrence of keywords, thematic mapping, co-citations and collaboration of authors and countries. The study used Biblioshiny as a tool to carry out the performance analysis and science mapping analysis.

The results show that the number of publications has significantly increased in the past decade, 88.4% of authors contribute at least a single article, 8.3% of authors published two articles, 2% of the authors published three documents and 0.6% of the authors contribute four papers. The USA, China and Australia were the most productive countries in terms of the total number of citations and foreign collaborations. Journal of Knowledge Management, Knowledge Management Research and Practice, VINE Journal of Information and Knowledge Management and International Journal of Technology Management are the top outlets in the knowledge management literature.

Over the past decade, the research on knowledge management construct has exploded because of the growing interest of researchers and practitioners in the field. Despite being a well-developed field, few studies have applied bibliometric analysis in the knowledge management literature. The study is more comprehensive in terms of the actors and methods involved in analyzing the scientific production of articles in the area of knowledge management.

Image Processing is an emerging field that is used to extract information from images. In recent years, this field has received immense attention from researchers, especially in the research domains of object detection, Biomedical Imaging and Semantic segmentation. In this study, a bibliometric analysis of publications related to image processing in the Science Expanded Index Extended (SCI-Expanded) has been performed. Several parameters have been analyzed such as annual scientific production, citations per article, most cited documents, top 20 articles, most relevant authors, authors evaluation using y-index, top and most relevant sources (journals) and hot topics.

The Bibliographic data has been extracted from the Web of Science which is well known and the world's top database of bibliographic citations of multidisciplinary areas that covers the various journals of computer science, engineering, medical and social sciences.

The research work in image processing is meager in the past decade, however, from 2014 to 2019, it increases dramatically. Recently, the IEEE Access journal is the most relevant source with an average of 115 publications per year. The USA is most productive and its publications are highly cited while China comes in second place. Image Segmentation, Feature Extraction and Medical Image Processing are hot topics in recent years. The National Natural Science Foundation of China provides 8% of all funds for Image Processing. As Image Processing is now becoming one of the most critical fields, the research productivity has enhanced during the past five years and more work is done while the era of 2005–2013 was the area with the least amount of work in this area.

This research is novel in this regard that no previous research focuses on Bibliometric Analysis in the Image Processing domain, which is one of the hot research areas in computer science and engineering.

This study aims to analyze the adoption of open access (OA) publishing in social sciences within central universities in India, focusing on various aspects such as the growth of OA literature, the use of different OA routes and collaboration patterns in OA publications.

Ten central universities were selected based on their rankings in the National Institute Ranking Framework 2022. Data on OA publishing in social sciences were collected from the Social Science Citation Index of the Web of Science (WoS) database using the advanced search query “(CU=India OR AD=India) AND PY=(2003–2022) NOT PY=(2023).” Data analysis was conducted using MS Excel (v16.0), BibExcel (version 2017), Biblioshiny (version 4.1.2) and Google Open Refine (version 3.7).

The study found that 30.40% of total publications were OA, with BHU as leading institute in OA publishing. OA publishing in social sciences saw a consistent increase, peaking in 2022 with 209 publications. “Sustainability” and “Plos One” were among the top ten journals, with 103 and 34 OA papers, respectively. OA publications had a higher mean citation rate than closed access publications. Collaboration with seven and nine authors had higher mean citation rates, while six-author collaborations were lower. Indian researchers received the most citations collaborating with the USA, UK and Australia. The Netherlands and Saudi Arabia received the fewer citations, when collaborating with Indian authors.

The study’s main limitation is its reliance on WoS data, excluding many OA publications from smaller or specialized journals. Additionally, the focus on high-ranked central universities may not represent the entire academic landscape, as OA publishing patterns vary across other institutions and disciplines.

The study’s findings suggest that advancing OA publishing in social sciences at Indian universities requires raising awareness of OA concepts, enhancing institutional support and policies and informing researchers about funding opportunities. Emphasizing Gold OA and funding publication fees can broaden access to research. Universities with low OA ratios should adopt similar policies, mandate public research deposits and develop technical infrastructure. Encouraging multi-author collaborations can boost research impact and citation rates. Insights from the study can help institutions and policymakers shape effective OA strategies, enhancing the visibility and impact of social science research.

This is the first study analyzing the adoption of OA in the field of social sciences in high-ranked central universities in India. It has implications for promoting OA and increasing accessibility to research outputs. Universities with higher OA ratios can lead in this regard and encourage others to adopt similar practices for overall OA growth.

This study aims to investigate the impact of ResearchGate (RG) scores on the scientific indicators of Qur’anic productions in Scopus.

This research is fundamental in method, created in a descriptive method and a scientometric approach. The statistical society includes 4,105 records produced by writers in the field of Qur’an during the time period of 2011–2020 indexed in the Scopus database. In this study, Pearson correlation coefficient test is used with aid of Excel and SPSS software.

Countries such as Malaysia, the USA and Indonesia, respectively, hold the highest number of scientific productions in the field of Qur’an. Iran holds the fourth place with a 544 record difference in comparison to Malaysia (866 documents). There is a positive and meaningful relation between measures of RG, readers, followers, citations and the H-index score regarding writers with received citations and the H-index score of scientific productions in the field of Qur’an in Scopus. However, no relation can be observed between the mentioned measures and indicators of the number of documents with cowriting.

Because of some authors not using the same name in their articles, it was not possible to access their profile in RG. For this reason, the information of these authors was not accessible in RG.

The activity of researchers in social networks will receive feedback from readers. This will result in more citations. Contrary to expectations, the research results showed that Iran does not have a good position in publishing Qur’anic works. Therefore, researchers should publish their findings in international journals.

Iranian writers should try to publish their scientific productions in international publications and also widely spread their content and research results across social networks to increase feedback and gain the attention of readers. This process leads to receiving reader feedback and publication of the Islamic teachings.

The relationship between the number of citations of Qur’anic works in Scopus and altmetric indicators in RG has not been investigated in previous researches. Therefore, this research is innovative in this field.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

This study aims to investigate the research productivity in terms of publications count of the top four premiers Indian Institute of Management (IIM) institutions and to explore the current research trends.

Bibliometric techniques were employed to assess the performance in terms of research productivity of authors affiliated with IIMs. The Elsevier Scopus database was selected as a tool to extract the prospective publications data limiting the time frame for 2010–2021. The IIM-Ahmedabad, IIM-Bangalore, IIM-Calcutta and IIM-Lucknow have been selected for the study. The harvested data were analyzed by using the standard bibliometric indicators and scientometric parameters to measure the research landscape such as average growth rate, compound average growth rate, relative growth rate, doubling time, degree of collaboration, collaborative index, collaborative coefficient and modified collaborative coefficient. VOSviewer 1.6.17, BibExcel and Microsoft Excel were used for data analysis and visualization.

The research productivity of selected four IIMs has shown an upward trend during the study period from 2010–2021 and accrued 4,397 publications with an average of 366 publications per year. The authorship patterns demonstrate the collaborative trends as most of the publications were produced by the multiple-authors (81.03%). IIM-Ahmedabad has produced the maximum number of publications (32.20%). The research productivity of IIMs has come out in collaboration with the 125 nations across the world and the USA, the UK, Canada, Germany and China are the front runners with IIMs in the collaborative network. The high magnitude and density of collaboration are evident from the calculated mean values of the degree of collaboration (0.82). The mean values of the collaborative index (2.64), collaborative coefficient (0.51) and modified collaborative coefficient (0.51) demonstrated a positive trend, but indicate the fluctuation in the collaborative pattern as time proceeds.

The study is limited to the publications data indexed in the Scopus database, therefore the outcome may not be generalized across other databases available in the public domain like Web of Science (WoS), PubMed, Dimensions and Google Scholars.

The findings of the study may aid academics and library professionals in identifying research trends, collaboration networks and evaluating other academic and research institutions by using the current advancement in data analysis.

The present study is the first effort to evaluate the research productivity of IIMs. The expanding literature will make an important contribution to identifying patterns and evaluating current research trends on a worldwide scale.