Purpose: This study aims to analyze academic research on Artificial Intelligence (AI) applications and tools in academic libraries, focusing on publications from the Scopus database between 2014 and 2024.
Design/methodology/approach: The study adheres to the PRISMA protocol, using VOSviewer, Bibliometrix, and Rstudio’s Biblioshiny function for bibliographic analysis and visualization.
Findings: The study highlights how the potential of AI in academic libraries may be increased by changing user needs and technical advancements. It comprises four thematic clusters: foundational technologies (machine learning, natural language processing, and automation), emerging innovations (generative AI), user-centric applications (chatbots), and the importance of AI literacy. It also reveals research gaps in automation and strategic AI integration, providing recommendations for improving library services.
Research limitations: The study is limited to articles published between 2014 and 2024 in the Scopus database, potentially excluding previous foundational work and research from other sources.
Practical implications: The study offers policymakers and library practitioners insightful information on effectively utilizing AI tools. This may result in overlooking earlier foundational work and research from multiple sources.
Originality/value: The study discovers the role of artificial intelligence (AI) in modernizing academic libraries, identifying research gaps, and providing strategic insights to improve technology and user experience.

Purpose: This paper examines African Journals Online (AJOL) as a bibliometric resource, providing a structured dataset of journal and publication metadata. In addition, it integrates AJOL data with OpenAlex to enhance metadata coverage and improve interoperability with other bibliometric sources.
Design/methodology/approach: The journal list and publications indexed in AJOL were retrieved using web scraping techniques. This paper details the database construction process, highlighting its strengths and limitations, and presents a descriptive analysis of AJOL’s indexed journals and publications.
Findings: The publication analysis demonstrates a steady growth in the number of publications over time but reveals significant disparities in their distribution across African countries. This paper presents an example of the possibility of integrating both sources using author country data from OpenAlex. The analysis of author contributions reveals that African journals serve as both regional and international venues, confirming that African journals play a dual role in fostering both regional and global research engagement
Research limitations: While AJOL contains relevant information for identifying and providing insights about African publications and journals, its metadata are limited. Therefore, the kind of analysis that can be performed with the database presented here is also limited. The integration with OpenAlex aims to overcome some of the limitations. Finally, although some automatic citation procedures have been performed, the metadata has not been manually curated. Therefore, if errors or inaccuracies are present in the AJOL, they may be reproduced in this database.
Practical implications: The database introduced in this article contributes to the accessibility of African scholarly publications by providing structured, accessible metadata derived from the AJOL. It facilitates bibliometric analyses that are more representative of African research activities. This contribution complements ongoing efforts to develop alternative data sources and infrastructure that better reflect the diversity of global knowledge production.
Originality/value: This paper presents a novel database for bibliometric analysis and offers a detailed report of the retrieval and construction procedures. The inclusion of matched data with OpenAlex further enhances the database’s utility. By showcasing AJOL’s potential, this study contributes to the broader goal of fostering inclusivity and improving the representation of African research in global bibliometric analyses.

Purpose: With the growth of knowledge and increasing competition, the assessment of scientific articles has become a challenging issue. Previous research suggests that multiple variables influence the number of academic articles. In this study, we aimed to evaluate the relationship between the beginning of chancellorship in top-ranked universities and the number of chancellors’ articles.
Design/methodology/approach: Chancellors of 200 top universities worldwide were randomly selected from the top 1,000 universities listed on the topuniversities.com profile page. Data were collected through the Scopus Database using a checklist that contained variables such as gender, age, being active or non-active, and continent. The mean number of articles during the period of three years before the beginning of the chancellorship until three years after that was compared using the Friedman test.
Findings: Considering the starting point of the chancellorship, the data showed that the mean number of published articles per year decreased significantly after beginning the chancellorship. Among the chancellors, active chancellors (having a minimum of one article each year), male chancellors, and those from North America indicated a decrease in the number of publications.
Research limitations: A major limitation was that in some universities, governance falls under vice-chancellor(s) rather than chancellor (s).
Practical implications: The study underscores the difficulty of balancing administrative responsibilities, such as university chancellorship, with academic pursuits.
Originality/value: For the first time, the results revealed that beginning chancellorship negatively impacts publication output.

Purpose: This study analyzes the profiles of elite Brazilian researchers, recognized through the prestigious CNPq productivity scholarships. By identifying distinct researcher clusters, the study sheds light on different academic strategies, levels of productivity, and academic contributions within the Brazilian higher education system.
Design/methodology/approach: The research analyzes a comprehensive dataset of 14,003 researchers, employing principal component analysis (PCA) followed by cluster analysis to group researchers based on their academic attributes. The clusters reflect diverse aspects of research productivity, graduate supervisions, and publication patterns.
Findings: The analysis reveals the existence of three distinct researcher profiles (the Advanced Supervisors, the Book Publishers/Organizers, and the Generalists). The study also highlights the characteristics of high-caliber scientists, representing the upper echelon of Brazilian researchers in terms of productivity and impact.
Research limitations: Although the study provides a robust analysis of the Brazilian system, the results reflect specific characteristics of the Brazilian academic context. Furthermore, the analysis was restricted to normalized annual data, which may overlook temporal variations in researcher productivity.
Pratical implications: The findings provide valuable insights for policy makers, funding agencies (such as CNPq), and university administrators who aim to develop tailored support programs for different researcher profiles.
Originality/value: The cluster-based profiling offers a novel perspective on how different academic trajectories coexist within a national science system, offering lessons for other emerging economies.

Purpose: This paper presents a new semi-automatic methodology for identifying inter-actor relationships by discerning viewpoints in non-social, political textual corpora. Although previous research has successfully discerned viewpoints, biases, and affiliations based on textual features, the task of relationship analysis in the absence of interactional data remains unaddressed.
Design/methodology/approach: We introduce a new paradigm for topic representation as a dynamic, continuous, multi-viewpoint spectrum based on the representation of viewpoints as vectors that capture common topical themes. As a proof of concept, we applied this paradigm to scrutinize the inter-state relationships reflected in the speeches of the UN General Assembly Debate Corpus (UNGDC).
Findings: The proposed paradigm effectively identifies discursive trends in UNGDC. Our analysis reveals common attitudes towards the topic and their prominence among different groups of actors and facilitates the analysis of relationships between actors through a quantitative representation of viewpoint similarity. The method also successfully captured temporal shifts in viewpoints and overall discourse trends, correlating with major geopolitical events.
Research limitations: One limitation of this study is the method’s sensitivity to data sparsity, which can skew viewpoint representations in cases of low topic involvement.
Practical implications: The proposed paradigm can be utilized by scholars in political science and other domains as a tool for semi-automated unsupervised textual analysis of various non-social textual sources, enabling the discovery of latent relationships between actors and the modeling of viewpoints in complex topics.
Originality/value: This study presents a novel framework for unsupervised semi-automatic textual analysis of relationships in non-social corpora through a new approach for the representation of viewpoints as thematic vectors.

Purpose: Despite the global shutdown of universities and research laboratories in 2020 due to the COVID-19 pandemic, a significant and unexpected increase in scientific production was observed during 2020 and especially in 2021 (Rousseau et al., 2023). A plausible explanation is that researchers took advantage of the lockdown period to write and develop pre-existing ideas. But what happened once that stockpile of ideas was exhausted?
Design/methodology/approach: This study aims to address that question by analyzing the scientific output of fourteen highly productive countries using data from three databases: WoS, Scopus, and OpenAlex.
Findings: Our analysis shows that, following the production peak in 2021, there was a general decline over the next two years (2022 and 2023) across most Western countries, including Japan and Brazil. However, this trend was not observed in China or India, which have maintained sustained growth since 2021. Russia, by contrast, has shown a continuous decline since 2021, likely related to its involvement in armed conflicts. Notably, this pattern of decline persists even when excluding the broad category of Life Sciences and Biomedicine.
Research limitation: The observed phenomenon cannot be fully explained. A broader understanding would require the wide distribution of a questionnaire among researchers and institutions.
Practical implications: This study provides insight into how the scientific system responded through its publication output to the temporary suspension of research institutions’ activities during the COVID-19 lockdown.
Originality/value: Our analysis contributes to understanding the unusual trends in research publications due to the pandemic’s influence. It can be seen as a discussion of a natural experiment in the science of science.

Purpose: To gain insights into the levels of training and support in research integrity and publishing ethics, levels of experience in publishing in scholarly journals and use of third-party manuscript preparation/editing services (which can include paper mills), and also to assess levels of awareness regarding different types of publishing ethics misconduct, we surveyed members of the Chinese Academy of Sciences (CAS) Journal Ranking WeChat channel.
Design/methodology/approach: The online survey collected voluntary anonymous responses from members of the CAS Journal Ranking WeChat channel, one of largest channels of Chinese researchers at all career stages within STM and social sciences. The respondents of the survey fell into one of the following categories: Undergraduate student, Master’s student, PhD candidate, Researcher, Research manager, Researcher with research management responsibilities, and Librarian. The survey included 14 main questions on the topics of access to research integrity and publishing ethics training, experience levels in publishing in scholarly journals (including using third-party services), authorship experiences and behaviours, levels of concern about different types of research integrity issues, and perceptions on who the respondents think are primarily responsible for upholding research integrity standards and training in publishing ethics. After applying inclusion criteria, 1,777 responses were included in the analysis.
Findings: Amongst the 1,777 respondents included in the study results, only 55.4% had any access to training in research integrity and publishing ethics, and an even smaller proportion to formal training. Even amongst cohorts with access to training (where respondents in the Researcher cohort have the highest access), answers to the questions on authorship and third-party services reveal many areas of confusion regarding authorship criteria and responsibilities in publishing ethics. In particular, the responses also show limited knowledge in recognising unethical service offerings by third-party services (e.g. adding authors, citations and data/images). The survey responses also show that even though respondents in the undergraduate cohort are already actively publishing articles as well as using third-party manuscript preparation/editing services, they have limited access to training and have high levels of uncertainty about authorship responsibilities. Out of all key stakeholders, respondents perceive research institutions to be mainly responsible for upholding research integrity standards as well as providing access to training.
Research limitations: As with all voluntary online surveys, the study design includes inherent limitations due to the self-reported nature of the responses. The respondents who participate are likely to have a particular interest and a higher level of awareness about the survey topic, and so the self-selecting nature of the participants can introduce personal biases, which can affect the overall results. This survey was sent to members of a WeChat channel focused on journal rankings, which also discusses research integrity issues, so the respondents may not provide a general representation of their career stage/subject discipline cohorts. The sample sizes were not comparable across all cohorts, so direct comparisons could not always be made. Instead, where appropriate, separate comparisons were made between Undergraduate students, Master’s students, PhD candidates and Researchers (29.26%-18.68% of respondents), or between Research managers, Researcher with research management responsibilities and Librarians (4.28%-2.53% of respondents).
Practical implications: It is important to ensure that research integrity and publishing ethics training and education needs are being met for researchers at all levels, including undergraduates. Findings from the survey highlight the importance of establishing training and education programmes tailored towards addressing specific areas of common confusion or limited awareness, especially to reduce the risk of unintentional misconduct. The findings from this survey can be used to inform training and education partnerships and collaborations across key stakeholders, including research institutions and publishers, so that we can collectively improve the overall integrity of scholarly publishing. A table of recommendations and a hypothetical case have been included to illustrate how this can be achieved.
Originality/value: To our knowledge, this is the first survey on this topic developed via a collaboration between the research integrity team at an international scholarly publisher and scientometrics researchers based in China. Sharing our perspectives and experience to develop the survey questions has helped to highlight the common areas of confusion regarding authorship responsibilities and ethical third-party service offerings within researchers in China, even amongst those who do have access to training.

Purpose: This study examines why papers with high CD indices (measuring research disruptiveness) increasingly show reduced citation impact and investigates whether this represents genuine impact reduction or methodological artifacts.
Design/methodology/approach: We analyzed 29 million papers (1950-2016) using Poisson regression to examine relationships between the CD index and citation count, with controls for fields, team size, and reference count.
Findings: Papers with high CD indices showed reduced citation impact over time. However, when controlling for increasing reference counts in papers, this relationship reversed, revealing a positive association. Papers with more references exhibit lower CD indices owing to the index’s sensitivity to the reference count, while achieving higher citation counts. Alternative innovation metrics consistently show positive correlations with citation impact.
Research limitations: The approach may not adequately capture the reduced citation impact of highly disruptive papers with fewer references. The analysis is limited to journal articles and shows correlation rather than causality.
Practical implications: The apparent undervaluation of disruptive research stems from methodological artifacts in the CD index calculation driven by evolving reference patterns. Researchers should control for the reference count when using this metric.

Purpose: Citation-based assessments of countries’ research capabilities often misrepresent their ability to achieve breakthrough advancements. These assessments commonly classify Japan as a developing country, which contradicts its prominent scientific standing. The purpose of this study is to investigate the underlying causes of such inaccurate assessments and to propose methods for conducting more reliable evaluations.
Design/methodology/approach: The study evaluates the effectiveness of top-percentile citation metrics as indicators of breakthrough research. Using case studies of selected countries and research topics, the study examines how deviations from lognormal citation distributions impact the accuracy of these percentile indicators. A similar analysis is conducted using university data from the Leiden Ranking to investigate citation distribution deviations at the institutional level.
Findings: The study finds that inflated lower tails in citation distributions lead to undervaluation of research capabilities in advanced technological countries, as captured by some percentile indicators. Conversely, research-intensive universities exhibit the opposite trend: a reduced lower tail relative to the upper tail, which causes percentile indicators to overestimate their actual research capacity.
Research limitations: The descriptions are mathematical facts that are self-evident.
Practical implications: The ratios between the number of papers in the global top 10% and 1% by citation count to the total number of papers are commonly used to describe research performance. However, due to variations in citation patterns across countries and institutions with reference to the global pattern, these ratios can be misleading and lose their value as research indicators.
Originality/value: Size-independent research performance indicators, obtained as the ratios between paper counts in top percentiles and the total numbers of publications, are widely used by public and private institutions. This study demonstrates that the use of these ratios for research evaluations and country rankings can be highly misleading.

Purpose: Policies have often, albeit inadvertently, overlooked certain scientific insights, especially in the handling of complex events. This study aims to systematically uncover and evaluate pivotal scientific insights that have been underrepresented in policy documents by leveraging extensive datasets from policy texts and scholarly publications.
Design/methodology/approach: This article introduces a research framework aimed at excavating scientific insights that have been overlooked by policy, encompassing four integral parts: data acquisition and preprocessing, the identification of overlooked content through thematic analysis, the discovery of overlooked content via keyword analysis, and a comprehensive analysis and discussion of the overlooked content. Leveraging this framework, the research conducts an in-depth exploration of the scientific content overlooked by policies during the COVID-19 pandemic.
Findings: During the COVID-19 pandemic, scientific information in four domains was overlooked by policy: psychological state of the populace, environmental issues, the role of computer technology, and public relations. These findings indicate a systematic underrepresentation of important scientific insights in policy.
Research limitations: This study is subject to two key limitations. Firstly, the text analysis method—relying on pre-extracted keywords and thematic structures—may not fully capture the nuanced context and complexity of scientific insights in policy documents. Secondly, the focus on a limited set of case studies restricts the broader applicability of the conclusions across diverse situations.
Practical implications: The study introduces a quantitative framework using text analysis to identify overlooked scientific content in policy, bridging the gap between science and policy. It also highlights overlooked scientific information during COVID-19, promoting more evidence-based and robust policies through improved science-policy integration.
Originality/value: This paper provides new ideas and methods for excavating scientific information that has been overlooked by policy, further deepens the understanding of the interaction between policy and science during the COVID-19 period, and lays the foundation for the more rational use of scientific information in policy-making.

Purpose: The study examines the synergy and hysteresis in the evolution of funding and its supported literature, depicts their temporal correlation mechanism, which aids in improving trend predictions.
Design/methodology/approach: The study uses the LDA model to identify topics in funding texts and supported papers. A cosine similarity algorithm was employed to estimate the nexus between topics and construct the topic evolution time series. Similarly, the hysteresis effect in topic evolution is analyzed based on topic popularity and content, leading to insights into their temporal correlation mechanism.
Findings: The study finds that fund and sponsored paper topics exhibit strong collaboration with a noticeable lag in evolution. The fund topics significantly influence sponsored paper topics after a two-year lag. Moreover, the lag effect is inversely proportional to the topic’s similarity.
Research limitations: We use the LDA model to determine the hysteresis effect in topic evolution despite its limitations in handling long-tail words and domain-specific vocabulary. Furthermore, the timing of the emergence of the focal topic in funds is undermined, affecting the findings.
Practical implications: These findings enhance the accuracy and scientific validity of trend prediction. Estimating and identifying patterns can help technology managers anticipate future research hotspots, supporting informed decision-making and technology management.
Originality/value: This study introduces a research framework to quantitatively and visually analyze the hysteresis effect, revealing the correlation and evolutionary patterns between fund research topics and their funded papers.