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The purpose of this paper is to know whether the authors’ productivity pattern of library and information science (LIS) open access journals adheres to Lotka’s inverse square law of scientific productivity. Since the law was introduced, it has been tested in various fields of knowledge, and results have varied. This study has closely followed Lotka’s inverse square law in the field of LIS open access journals to find a factual result and set a baseline for future studies on author productivity of LIS open access journals.

The publication data of selected ten LIS open access journals pertain to authorship, citations were downloaded from the Scopus database and analysed using bibliometric indicators like authorship pattern, collaborative index (CI), degree of collaboration (DC), collaborative coefficient (CC) and citation counts. This study has applied Lotka’s inverse square law to assess authors’ productivity pattern of LIS open access journals and further Kolmogorov-Smirnov (K-S) goodness-of-fit test applied for testing of observed and expected author productivity data.

Inferences were drawn for the set objectives on authorship pattern, collaboration trend and authors’ productivity pattern of LIS open access journals covered in this study. The single authorship pattern is dominant in LIS open access journals covered in this study. The CI, DC and CC are found to be 1.95, 0.47 and 0.29, respectively. The expected values as per Lotka’s law (n = −2) significantly vary from the observed values as per the chi-square test and K-S goodness-of-fit test. Hence, this study does not adhere to Lotka’s inverse square law of scientific productivity.

Researchers may find an idea about the authors’ productivity patterns of LIS open access journals. This study has used the K-S goodness-of-fit test and the chi-square test to validate the authors’ productivity data. The inferences found out from this study will be a baseline for future research on author productivity of LIS open access journals.

This study is significant from the viewpoint of the growing research on open access journals in the field of LIS and to identify the authorship pattern, collaboration trend and author productivity pattern of such journals.

This study aims to analyze the productivity patterns of authors using law literature indexed in Directory of Open Access Journals (DOAJ) from 2016 to 2020 based on Lotka’s law. Lotka’s law of scientific productivity provides a platform for studying the variation between the actual and expected authors’ productivity patterns in a subject area over a specified period.

This study covers 3,334 open access journal articles in law subject. The law journals are subdivided into two basic divisions, namely, public law and private law. This paper focuses on the journal-wise distribution of publications, subject-wise distribution of publications, annual growth rate (AGR) as well as compound AGR and applicability of Lotka’s law in both public and private law by applying the least square method followed by Pao and doing the K-S goodness-of-fit test. Student’s t-test and chi-square test have been applied to verify the significant difference between the public law and the private law literature.

There is no significant difference between the public law and private law publications on their publications per issue. The chi-square test showed that there is no significant difference between the year-wise publications in public law and private law. The authorship productivity in public law differs from the distribution of Lotka’s inverse square law, whereas it follows Lotka’s law in the case of private law.

This study is based on the articles published in open access English language journals which are indexed in the DOAJ.

This study will be useful to know the authorship productivity pattern of law literature for both public and private law individually.

This study aims to analyze the productivity patterns of authors in Nigeria using publications indexed in Medline from 2008 to 2012 based on Lotka’s Law. Lotka’s Law of scientific productivity provides a platform for studying inequality in authors’ productivity patterns in a given field and over a specified period.

This study covers all the journal articles on HIV/AIDS pandemic in Nigeria over a period of five years (2008-2012) in Medline, of which 512 articles were reported to have been published during this period. In this paper, 306 articles that had HIV/AIDS in the title, published in 20 journals, and articles that had HIV/AIDS as author keywords were analyzed. Because no local database that indexed biomedical literature from Nigeria was available, Medline was used, which is not only a robust and flexible database that includes articles from Nigeria but is also the largest medical database that indexes over six-and-a-half million articles from 3,400 biomedical journals.

While HIV/AIDS can be considered a global pandemic, Nigeria has the second highest number of new infections reported each year, and an estimated 3.7 per cent of the population is living with the dreaded disease. This study presents a general picture of the distribution of papers as single-author papers, multiple-author papers and the measures of co-authorship. The findings of the study reveal that in the productivity distribution for authors on the subject of HIV/AIDS, only co-authors and non-collaborative authors’ categories fit in the Lotka’s Law, whereas all-authors and first-author categories differ from the distribution of Lotka’s inverse square law.

The empirical evidence used in this paper was based on only articles of HIV/AIDS pandemic in Nigeria that had HIV/AIDS the title. Therefore, the findings of this study might not be the generalized to other biomedical research studies.

The originality of this paper lies in the fact that the productivity pattern of each of the different author categories on the subject of HIV/AIDS is a first of its kind in the Nigerian context.

The purpose of this paper is to examine the classic characteristics of highly cited articles (HCAs) of top-ranked library and information science (LIS) journals and get acquainted with the high-quality works in specific areas of LIS for distinguishing what gets cited and who the prolific authors are.

The HCAs published across the top four LIS journals were downloaded, coded and a database was developed with basic metadata elements for analysis using bibliometric indicators. Lotka’s Inverse Square Law of Scientific Productivity was applied to assess the author’s productivity of HCA. The content analysis method was also used to find out the emerging areas of research that have sought high citations.

Inferences were drawn for the proposed five number of research questions pertaining to individual productivity, collaboration patterns country and institutional productivity, impactful areas of research. The Netherland found to be the potential player among all the affiliating countries of authors and Loet Leydesdorff tops the list among the prolific authors. It is observed that Lotka’s Classical Law also fits the HCA data set in LIS. “Research impact measurement and research collaboration,” “Social networking” and “Research metrics and citation-based studies” are found to be the emerging areas of LIS research.

Researchers may find a way what gets cited in specific areas of LIS literature and why along with who are the prolific authors.

This study is important from the perspective of the growing research field of the LIS discipline to identify the papers that have influenced others papers as per citation count, spot the active and more impactful topics in LIS research.

This study aims to sketch a bibliometric portrait of the International Journal of Innovation Science (IJIS) and attempts to evaluate its publication patterns from 2011 to 2020 by unfolding the key aspects of its publication trends for the audience of the journal and scholars of bibliometric studies as well.

This study analyzes papers published in the IJIS from 2011 to 2020 by using the required bibliometric measures to analyze the key aspects of the publishing trends of IJIS.

This study finds that a total of 487 authors published 271 articles in IJIS during 2011–2020. The USA leads the table with 89 papers followed by India (29 papers) and China (26 papers). The degree of collaboration in IJIS ranged from 0.36 to 0.94. Moreover, this study finds that the keyword “design/methodology/approach” is the central theme of research in IJIS around which all other keywords revolve.

This study focuses on the publication patterns of the IJIS over a period of ten years. Patterns of research output in 271 publications are comprehended and analyzed. For making a ten-year bibliometric study, the papers published before 2011 were excluded from the purview of research.

Readers of the IJIS, teachers and research scholars interested in bibliometric studies can benefit from insights into the scholarly papers published in IJIS from 2011 to 2020.

This study would provide the readers of IJIS to ascertain significant contributions, top cited papers, the most prolific authors, geographical distribution of papers, keyword co-occurrence and bibliographic coupling.

The aim of this paper is to investigate the scholarly communications in open access journals of library & information science and to study the key dimensions of these publications.

For the analysis of the study, top ten open access journals of 2011, which were indexed in SCOPUS, have been selected. The authors employed necessary bibliometric measures to analyze different publication parameters.

It is found that the contribution of articles in these top ten open access journals in 2011 is good, i.e. 37.3 percent. Single authored papers are found to be the highest (40.48 percent), followed by two-authored and then three-authored papers. The degree of collaboration is found to be between 0.33 and 0.8. The numbers of citations used in the paper are also good (average 21.48 percent paper). In regards to ranking of country productivity, the USA topped the list.

This paper focuses on the publication traits of top ten open access journals of library & information science of the year 2011. A total of 373 papers from these ten journals are analyzed. Further studies can include more open access journals of this field for a period of more than one year.

Scholars can benefit from insights into the scholarly contributions of top ten open access journals of 2011 in the field of library & information science.

This paper provides valuable insights into the nature of academic publishing of open access journals of library & information science. It can help the researchers, professionals, teachers and students to understand the top open access journals, valuable contributions, highly cited journals, country productivity, and other parameters.

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.

Mucormycosis has evolved as a post-COVID-19 complication globally, especially in India. The research on fungus has been very primitive, and many scientific publications have been discovered. The current COVID-19 pandemic needs further investigation into this unusual fungal infection. This review study aims to provide a pen-picture to researchers, science policymakers and scientists about different bibliometric indicators related to the research literature on mucormycosis.

The quantitative research was conducted using the established procedure of bibliometric investigation on data collected from Scopus from 2011 to 2020 using a validated search query. The search query consisted of keywords “Mucormycosis” or “Mucormycoses” or “Mucormycose” or “Mucorales Infection” or “Mucorales Infections” or “Black Fungus Infection” or “Black Fungus Infections” or “Zygomycosis” in the “Title-Keyword-Abstract” search option for data extraction. The analysis of data is performed using MS-Excel. Mapping was done with state-of-the-art visualization tools Biblioshiny and VOSviewer, using bibliometric indicators as units of analysis.

The analysis reveals that the first publication on this topic was reported from 1923 onwards. In total, 9,423 authors contributed 1,896 papers with 11,437 collaborated authors, documents per author are 0.201, authors per document are 4.97 and co-authors per document are 6.03. Total records were published in 779 journals in the English language from 75 countries globally. Mucormycosis literature is mostly open access, with 1,210 publications available via different open access routes. The highest number of articles (204) published in the journal “Mycoses” with 1,333 authors received 4,875 cited references, and the h-index has 24. The growth of publications is exponential, as depicted by the Price Law. The USA has recorded a maximum number of publications at both country and institutional levels compared to the other nations. There has been extensive research on mucormycosis before the outbreak as a post-COVID complication, as indicated by the highest number of publications in 2019.

The research hot spots have altered from “Mucormycosis,” “fungi,” “Zygomycosis” and “Drug efficacy”, “Drug Safety” to “Microbiology,” “Pathology,” “nucleotide sequence,” “surgical debridement” which indicates that potential area of research in the near future will be concerned with more extensive research in mucormycosis to develop standard treatment procedures to fight this infection. The quantity of scientific publications has also increased over time. The research and health community are called upon to join forces to activate existing knowledge, generate new insights and develop decision-supporting tools for health authorities in different nations to leverage vaccination in its transformational role toward successfully attaining nil cases of COVID-19.

The analysis of collaboration, findings, the research networks and visualization makes this study novel and separates from traditional metrics analysis. To the best of the authors’ knowledge, this work is original, and no similar studies have been found with the objectives included here.

The study identifies 621 authors who contributed 1,423 periodical articles and monograph publications to the geographical literature on Nigeria between 1901 and 1970. Publications/author relationship shows a perfect Bradford distribution comprising fifty‐three core authors having each six publications or more and among them contributing 38 per cent of all items. The significance of these results for retrospective bibliographical searches and their methodological implications for documentation studies in general are suggested and briefly discussed.