In the vast expanse of scientific literature, determining which researchers have made the most significant con- tributions to their field is essential. However, the scientific community lacks a standardized set of criteria for identifying impactful researchers. Existing platforms, like Google Scholar, Semantic Scholar & Web of Science, provide useful metrics like total publications, citation counts, and h-index, but no universally accepted frame- work exists to comprehensively evaluate a researcher’s true impact. This study proposes a novel framework for identifying impactful researchers within the computer science domain. The framework integrates 64 dis- tinct quantitative parameters across categories such as citation-based, publication-based, author-countbased, and age-weighted metrics to evaluate researchers’ contributions. Unlike traditional methods that focus on individual indicators, our framework provides a comprehensive evaluation model that considers multiple factors simulta- neously. The parameters were selected based on their importance scores, determined by their ability to classify awardees and non-awardees. Experiments were performed on a balanced dataset comprising 600 awardees and 600 non-awardees, yielding classification accuracies ranging from 57% to 78% in recognizing influential researchers. The top-ranked features from each parameter category effectively promoted 50% to 55% of awardees into the top 100 researcher rankings. These findings offer a robust tool for academic institutions and organiza- tions seeking to identify impactful researchers. The proposed framework enables more objective evaluation and provides actionable insights for individual researchers striving for recognition and influence in their field.

This article presents a scientometric portrait of Late Professor (Dr.) Hildrun Kretschmer, a renowned Scientometrician of world repute. As the founder of the COLLNET network, COLLNET Journal of Scientometrics and Information Management, and WISE Lab, Dr Kretchmer significantly contributed for the development of scientific collaboration and knowledge dissemination. This study is based on the data available in the “The ‘Social Gestalt’ of Scientific Communications: Festschrift in the honour of Hildrun Kretschmer”. The paper examines her publication output and citation patterns, collaboration networks, and highly cited papers, providing insights into her scholarly impact and influence. She published nearly 68 papers during the year 1979-2021, and 2008 was her most productive year. The journal “Scientometrics” a publication of Springer Nature was the most preferred journal for her publications. The results highlight her pioneering role in shaping the field of scientometrics and collaboration. Her contributions will continue to inspire future research in this area.

Traditionally our analysis has relied on press releases retrieved from a newspaper company-produced database, NikkeiTelecom21. In recent years, however, there has been a notable increase in press releases issued directly by universities, with only a portion included in this database. Our comparative study between NikkeiTelecom21 and the Nikkei Shimbun website revealed that, while the number of press releases in the former has declined since 2019, the latter has maintained a steady output. Furthermore, our investigation of press releases directly collected from the websites of four universities registered with the Science Portal showed substantial variation in their inclusion in Nikkei press releases—for example, while the University of Tokyo had an estimated coverage rate of over 80%, Hokkaido University’s rate was below 15%. This discrepancy points to potential biases in the dissemination of university press releases and highlights the need for broader representation and more comprehensive analysis in understanding how academic research is publicly communicated.

This article provides an in-depth examination of the emerging field of smart campuses and IoT by investigating the thematic landscape of existing literature. The study employs Latent Dirichlet Allocation (LDA) topic modeling to analyze the thematic landscape, identifying key research areas and themes. The dataset consists of 507 research articles retrieved from the Scopus database, covering the period from 2014 to 2023. The LDA model was optimized with α = 0.1 and β = 0.01, and the number of topics (K) was determined as 8 based on the c_v coherence score (0.393), ensuring robust topic extraction. This analysis offers a comprehensive overview of the current state of smart campuses and IoT research, revealing diverse research themes such as “Comprehensive Technology Integration and Management,” “Artificial Intelligence and Cloud-Based Systems,” “Educational Technologies and Innovative Applications,” “Low Power Networks,” “Smart Education Environments,” “Safe and Flexible Smart Campus Architecture,” “Energy Efficient Smart Buildings,” and “Sustainable Smart Education and Urban Development.” These themes highlight the complexity and multidimensionality of the research in this field. While the study provides valuable insights, it is important to acknowledge certain limitations, such as potential biases in dataset selection and the interpretative nature of topic modeling. Moreover, the LDA model’s dependence on predefined topic numbers might limit its ability to capture emerging research themes comprehensively. Future research could refine these findings by incorporating additional datasets, employing alternative modeling approaches such as Hierarchical Dirichlet Process (HDP), and integrating hybrid methodologies to enhance thematic robustness. The study’s findings underscore the diversity and richness of research themes, offering valuable insights for researchers and practitioners, and facilitating more targeted and effective future research and innovation.

The role of women has transformed from primary caregivers to primary earners in the society. The growth of studies on women’s issues has been continuous research since decades. The research interest in unpaid work has seen increased collaboration, profound familiarity with influential authors, and access to relevant literature, especially for new researchers focusing on this issue. The present paper has performed a bibliometric analysis and maps the research landscape based on the published literature on women’s unpaid work, using R-biblioshiny program and VOS viewer software. It analyses, citation patterns authorship and affiliation and other parameters. The study is based on 1281 articles on women’s unpaid work drawn from the Scopus database, published between 2001and 2024.The study on women’s unpaid labour shows a rising trajectory with an increased volume of productive growth. More citations are from “Feminist Economics” journal, and identified 10 authors, the most co-cited cluster of researchers in the said field. The authors’ affiliations include prestigious institutions such as the University of Oxford, Flinders University, Stockholm University, and Australian National University. The study finds international collaboration more among authors from the USA, India, Australia, the U.K., Spain, Germany and Canada. The study has identified important keywords in the area, that includes “time poverty,” “parenthood,” “informal care,” “time allocation,” and “work-life balance.”

After outlining the definition and functions of think tanks, we highlight the significant role played by McGann’s Think Tanks and Civil Societies Program (TTCSP). For years, they published rankings of think tanks based on different criteria. Since the United States hosts the most important think tanks globally, we explore several prominent examples, with a particular focus on the Brookings Institution. Additionally, we note a recent and notable rise in the number and influence of think tanks across Asia. Based on McGann’s data, we conducted a bibliometric analysis exploring the relationship between a country’s number of think tanks and its Gross Domestic Product (GDP). The results indicate a positive correlation, suggesting that economic capacity may support or incentivize the development of such organizations. Finally, we focus on think tanks in the Global South, using the Bangladesh Institute of Development Studies (BIDS) as a case study to explore their growing relevance in shaping policy and research agendas in a developing context.

Background: Predatory journals are fraudulent publications that feature unethical and inaccurate research works. Objective: This study aimed to check the ability of a machine learning tool to identify predatory journals when compared to manual methods. Methods and Material: A cross-sectional observational study design was opted for. After data collection and screening of 23 journals, 19 journals were chosen for evaluation. These journals featured research in pediatric dentistry between 2016 and 2023 from three western states of India. Each journal was analyzed through two manual methods [Predatory Rate (PR) and Patwardhan Protocol (PP)] and by a machine learning tool [(Academic Journal Predatory Checking system (AJPC)]. Statistical analysis was carried out using Orange Data Mining Software (3.36.0). A confusion matrix was drawn to calculate accuracy, precision, recall, and F1 score. A Cohen’s Kappa was calculated to evaluate the agreement of results beyond chance, followed by Mcnemar’s test of significance. Results: An F1 value of 0.96 suggests that AJPC nearly replicates the results of PP. However, this cannot be said when compared with PR, where an accuracy of only 68.42% is statistically significant (p<0.05). Conclusion: This is a first-of-its-kind study in the academic domain of pediatric dentistry that explores AJPC’s capability against manual methods to identify predatory journals. Preliminary results indicate a rising trend of predatory publishing in Western India. Further investigations in research malpractice can be explored through larger datasets across expanded geographical regions to overcome the limitations of this study.

The paper makes a bibliometric assessment of the scientific output of the Punjab Agricultural University (PAU) in agricultural sciences for a period of 20 years from 2003-2022. Data for the study were downloaded from the Scopus database of the Elsevier. To identify the papers published by the university, a search was conducted in the Scopus database using Punjab Agricultural University in the affiliation tag for the period 2003-2022. The downloaded data identified 6016 research publications published by PAU during the study period of 2003-2022. The growth pattern of publications output during the period under study is inconsistent but shows a growing trend of output. The highest number of articles was produced in the last two year block of 2021-2022. Of the total output, about 48.8% papers appeared in Indian journals and remaining 51.2% in journals originating from other developing and developed nations of the world. Only a small proportion of articles appeared in high and very high impact factor journals. “Agricultural Research Journal” published by the PAU was the most preferred choice of communication of research results by the scholars of the university. The study provides deep insights into research contributions and trends of output of the university and is the first study related to assess scientific productivity of PAU in agricultural sciences using different bibliometric indicators.

The gut-brain axis, a vital bidirectional communication system between the central nervous system and the gastrointestinal tract, is crucial for maintaining homeostasis. Dysregulation of this axis, influenced by factors like gut microbiota, neurotransmitters, and dietary patterns, is associated with various health conditions. This study presents a comprehensive bibliometric analysis of gut-brain axis (GBA) research. This study utilizes co-word cluster network analysis on 16062 publications from the Web of Science database to understand the thematic evolution of gut-brain axis studies. The top 20 countries, organizations, authors, journals and WoS micro topics were identified along with their publication impact in terms of average citation and h-index, were also analysed using the Bibliometrix-Biblioshiny package in R software. The findings show significant growth in publications that indicates the increasing importance of gut-brain axis research. Thematic analysis reveals a shift from microbiota characterization to metabolic, immune, and neuroinflammatory pathways, emphasizing translational applications such as probiotics and fecal microbiota transplantation (FMT). The increasing focus on neurodegenerative and psychiatric disorders emphasize the interdisciplinary nature of GBA research, spanning neuroscience, microbiology, and immunology.

An increasing number of articles are published in the field of optimization research, and response surface methodology is an interesting optimization tool. As a result, the main goal of this work is to conduct a bibliometric analysis on the distribution of response surface methodology-related articles across the different domains of optimization research, as well as to track the evolution of their interest and identify the nations, publishers, and authors producing the greatest volume of scholarly works. For this investigation, the “LENS” database system was used since it covers a huge number of documents and simplifies the process of downloading and analyzing datasets. VOSviewer and the text mining program Orange Canvas were used to analyze the dataset. The survey indicates that the most prolific countries in this field of study are those in Europe. The most publications are found in iop conference series and materials, whereas the most citations are found in the journal of bioresource technology. Additionally, according to authors, the most used method for experimental optimization is response surface methodology, or RSM. Despite having several benefits over the traditional one parameter at a time strategy, RSM is not appropriate for every modeling and optimization study.