Publications

19 pages, 2890 KiB

Open AccessArticle

Publication Trends on the Varying Coefficients Model: Estimating the Actual (Under)Utilization of a Highly Acclaimed Method for Studying Statistical Interactions

by Assaf Botzer

Publications 2025, 13(2), 19; https://doi.org/10.3390/publications13020019 - 7 Apr 2025

Abstract

Numerous papers have demonstrated that by using a varying coefficients model (VCM), researchers can unveil patterns of interactions between variables that could otherwise remain hidden if using the more popular regression model with an interaction term. Hence, one would expect high acceptance of [...] Read more.

Numerous papers have demonstrated that by using a varying coefficients model (VCM), researchers can unveil patterns of interactions between variables that could otherwise remain hidden if using the more popular regression model with an interaction term. Hence, one would expect high acceptance of the VCM as a tool for studying statistical interactions in datasets. Yet, the current paper shows that the VCM is still struggling to migrate from journals in which methods are presented to journals in which methods are utilized. First, a search in Google Scholar with the phrase “varying coefficients” returned ~79,200 results in comparison to returning ~2,710,000 results with the phrase “interaction term”. Second, a bibliometric analysis of publications with the VCM showed that in many research domains, there were more publications with the VCM in journals on methods than publications with the VCM in journals for empirical investigations. Economics and environmental studies stood out with many more publications with the VCM in empirical journals than in journals on statistical methods. The gap between the high acclaims of the VCM in the statistical literature and its low utilization rate in practice should be of concern to the research community. The possible reasons for this gap and its potential remedies are discussed. Full article

► Show Figures

Figure 1

28 pages, 365 KiB

Open AccessArticle

Tailoring Scientific Knowledge: How Generative AI Personalizes Academic Reading Experiences

by Anna Małgorzata Kamińska

Publications 2025, 13(2), 18; https://doi.org/10.3390/publications13020018 - 2 Apr 2025

Abstract

The scientific literature is expanding at an unprecedented pace, making it increasingly difficult for researchers, students, and professionals to extract relevant insights efficiently. Traditional academic publishing offers static, one-size-fits-all content that does not cater to the diverse backgrounds, expertise levels, and interests of [...] Read more.

The scientific literature is expanding at an unprecedented pace, making it increasingly difficult for researchers, students, and professionals to extract relevant insights efficiently. Traditional academic publishing offers static, one-size-fits-all content that does not cater to the diverse backgrounds, expertise levels, and interests of readers. This paper explores how generative AI can dynamically personalize scholarly content by tailoring summaries and key takeaways to individual user profiles. Nine scientific articles from a single journal issue were used to create the dataset, and prompt engineering was applied to generate tailored insights for exemplary personas: a digital humanities and open science researcher, and a mining and raw materials industry specialist. The effectiveness of AI-generated content modifications in enhancing readability, comprehension, and relevance was evaluated. The results indicate that generative AI can successfully emphasize different aspects of an article, making it more accessible and engaging to specific audiences. However, challenges such as content oversimplification, potential biases, and ethical considerations remain. The implications of AI-powered personalization in scholarly communication are discussed, and future research directions are proposed to refine and optimize AI-driven adaptive reading experiences. Full article

(This article belongs to the Special Issue AI in Open Access)

► Show Figures

Figure 1

21 pages, 1577 KiB

Open AccessArticle

Does Publisher Volume Matter? A Cross-Sectional Analysis of Scopus Journal Publishing Patterns

by Eungi Kim

Publications 2025, 13(2), 17; https://doi.org/10.3390/publications13020017 - 1 Apr 2025

Abstract

The objective of this study is to examine the relationship between publisher volume—the number of journals a publisher produces—and journal publishing patterns in Scopus, including various journal metrics such as the h-index, SCImago Journal Rank (SJR), and journal quartiles. The SCImago database, which [...] Read more.

The objective of this study is to examine the relationship between publisher volume—the number of journals a publisher produces—and journal publishing patterns in Scopus, including various journal metrics such as the h-index, SCImago Journal Rank (SJR), and journal quartiles. The SCImago database, which is derived from Scopus data, serves as a proxy for journal impact and influence. The analysis also considered factors such as Open Access (OA) status, geographical location, and subject areas. Using the 2023 SJR dataset, publishers were classified into four categories: V1 (single journal), V2 (2–9 journals), V3 (10–99 journals), and V4 (100+ journals). The findings showed that V4 publishers accounted for 44.5% of Scopus-indexed journals despite comprising only 0.3% of all publishers, whereas V1 publishers represented 78.6% of all publishers but contributed only 21.3% of journals. High-volume publishers had more journals ranked in Q1 and Q2, while lower-volume publishers were more concentrated in Q3 and Q4. Results from the linear mixed-effects model indicated that publisher volume was associated with journal metrics, with higher-volume publishers generally achieving higher h-index and SJR scores. Western Europe and North America had the highest number of V4 publishers, whereas China, Spain, and Italy exhibited strong journal production but had fewer publishers in the highest-volume category. These results illustrate the dominance of a small group of high-volume (V4) publishers and the challenges smaller publishers face in gaining visibility and impact. They also underscore the need to consider policies that foster a more balanced and equitable scholarly publishing environment, particularly for underrepresented regions and subject areas. Full article

► Show Figures

Figure 1

12 pages, 247 KiB

Open AccessArticle

From Fees to Free: Comparing APC-Based and Diamond Open Access Journals in Engineering

by Luís Eduardo Pilatti, Luiz Alberto Pilatti, Gustavo Dambiski Gomes de Carvalho and Luis Mauricio Martins de Resende

Publications 2025, 13(2), 16; https://doi.org/10.3390/publications13020016 - 1 Apr 2025

Abstract

This study analyzes the impact of different Open Access (OA) publication models in engineering, comparing journals that charge Article Processing Charges (APCs) with those operating under the Diamond OA model. A total of 757 engineering OA journals, comprising 504 APC-based and 253 Diamond [...] Read more.

This study analyzes the impact of different Open Access (OA) publication models in engineering, comparing journals that charge Article Processing Charges (APCs) with those operating under the Diamond OA model. A total of 757 engineering OA journals, comprising 504 APC-based and 253 Diamond OA journals, were examined using bibliometric data from 2020 to 2023. The analysis focused on four key metrics: CiteScore, total citations, number of published articles, and the percentage of cited articles. The results indicate that APC-based journals dominate the upper quartiles (Q1 and Q2) regarding absolute citation counts, primarily driven by high-volume mega-journals such as IEEE Access. However, Diamond OA journals exhibit a higher proportion of cited articles (88.8% compared to 83.4% in APC-based journals) within the top 10% category. Despite their benefits in providing cost-free dissemination, Diamond OA journals account for only 8.4% of the 3012 active engineering journals indexed in Scopus, highlighting sustainability and visibility challenges. The findings suggest that, while APC-based journals achieve higher absolute citation counts, editorial reputation and visibility strategies significantly influence citation performance. This study contributes to the ongoing discussion on the financial sustainability and equity of OA publishing in engineering. Full article

(This article belongs to the Special Issue Diamond Open Access)

25 pages, 7710 KiB

Open AccessArticle

Top2Vec Topic Modeling to Analyze the Dynamics of Publication Activity Related to Environmental Monitoring Using Unmanned Aerial Vehicles

by Vladimir Albrekht, Ravil I. Mukhamediev, Yelena Popova, Elena Muhamedijeva and Asset Botaibekov

Publications 2025, 13(2), 15; https://doi.org/10.3390/publications13020015 - 25 Mar 2025

Abstract

Unmanned aerial vehicles (UAVs) play a key role in the process of contemporary environmental monitoring, enabling more frequent and detailed observations of various environmental parameters. With the rapid growth of scientific publications on this topic, it is important to identify the key trends [...] Read more.

Unmanned aerial vehicles (UAVs) play a key role in the process of contemporary environmental monitoring, enabling more frequent and detailed observations of various environmental parameters. With the rapid growth of scientific publications on this topic, it is important to identify the key trends and directions. This study uses the Top2Vec algorithm for topic modeling algorithm aimed at analyzing abstracts of more than 556 thousand scientific articles published on the arXiv platform from 2010 to 2023. The analysis was conducted in five key domains: air, water, and surface pollution monitoring; causes of pollution; and challenges in the use of UAVs. The research method included data collection and pre-processing, topic modeling, and quantitative analysis of publication activity using indicators of the rate (D1) and acceleration (D2) of change in the number of publications. The study allows concluding that the main challenge for the researchers is the task of processing data obtained in the course of monitoring. The second most important factor is the reduction in restrictions on the UAV flight duration. Among the causes of pollution, agricultural activities will be considered as a priority. Research in monitoring greenhouse gas emissions will be the most topical in air quality monitoring, while erosion and sedimentation—in the area of land surface control. Thermal pollution, microplastics, and chemical pollution are most relevant in the field of water quality control. On the other hand, the interest of the scientific community in topics related to soil pollution, particulate matter, sensor calibration, and volatile organic compounds is decreasing. Full article

► Show Figures

Figure 1

25 pages, 747 KiB

Open AccessArticle

Generative AI vs. Traditional Databases: Insights from Industrial Engineering Applications

by Jose E. Naranjo, Maria M. Llumiquinga, Washington D. Vaca and Cristian X. Espin

Publications 2025, 13(2), 14; https://doi.org/10.3390/publications13020014 - 25 Mar 2025

Abstract

This study evaluates the efficiency and accuracy of Generative AI (GAI) tools, specifically ChatGPT and Gemini, in comparison with traditional academic databases for industrial engineering research. It was conducted in two phases. First, a survey was administered to 101 students to assess their [...] Read more.

This study evaluates the efficiency and accuracy of Generative AI (GAI) tools, specifically ChatGPT and Gemini, in comparison with traditional academic databases for industrial engineering research. It was conducted in two phases. First, a survey was administered to 101 students to assess their familiarity with GAIs and the most commonly used tools in their academic field. Second, an assessment of the quality of the information provided by GAIs was carried out, in which 11 industrial engineering professors participated as evaluators. The study focuses on the query process, response times, and information accuracy, using a structured methodology that includes predefined prompts, expert validation, and statistical analysis. A comparative assessment was conducted through standardized search workflows developed using the Bizagi tool, ensuring consistency in the evaluation of both approaches. Results demonstrate that GAIs significantly reduce query response times compared to conventional databases, although the accuracy and completeness of responses require careful validation. A Chi-Square analysis was performed to statistically assess accuracy differences, revealing no significant disparities between the two AI tools. While GAIs offer efficiency advantages, conventional databases remain essential for in-depth literature searches requiring high levels of precision. These findings highlight the potential and limitations of GAIs in academic research, providing insights into their optimal application in industrial engineering education. Full article

► Show Figures

Figure 1

20 pages, 251 KiB

Open AccessArticle

Diamond Open Access Landscape in Croatia: DIAMAS Survey Results

by Jadranka Stojanovski and Danijel Mofardin

Publications 2025, 13(1), 13; https://doi.org/10.3390/publications13010013 - 13 Mar 2025

Abstract

As open science initiatives address the crisis in scholarly communication driven by commercialisation, diamond open access publishing—promoting equity for authors and readers—has emerged as a focal point in open access scholarly publishing. This study examines the landscape of institutional publishing in Croatia, focusing [...] Read more.

As open science initiatives address the crisis in scholarly communication driven by commercialisation, diamond open access publishing—promoting equity for authors and readers—has emerged as a focal point in open access scholarly publishing. This study examines the landscape of institutional publishing in Croatia, focusing on the community-owned diamond open access model. Through the DIAMAS project survey, which targeted 251 institutional publishers and achieved a response rate of 77, the research identifies the distinct features of Croatian institutional publishing. Institutional publishers are characterised by governance structures, funding challenges, voluntary staffing, and alignment with open science principles. Notable traits include reliance on public funding, use of the national open access journal platform, and a strong diamond open access publishing tradition. Key findings emphasise the critical role of national infrastructure, services, and multilingual publishing. Persistent challenges include meeting indexing criteria, advancing open science practices, and ensuring metadata quality. This study provides a comprehensive mapping of Croatian institutional publishers, offering insights into their strengths and weaknesses while proposing strategies for improvement. The findings underscore the importance of national policy frameworks, capacity building, and international collaboration to ensure the sustainability and visibility of Croatian institutional publishing. Full article

(This article belongs to the Special Issue 10th Anniversary Special Issue "PUBMET2023 Conference on Scholarly Communication in the Context of Open Science")

23 pages, 665 KiB

Open AccessArticle

The Origins and Veracity of References ‘Cited’ by Generative Artificial Intelligence Applications: Implications for the Quality of Responses

by Dirk H. R. Spennemann

Publications 2025, 13(1), 12; https://doi.org/10.3390/publications13010012 - 12 Mar 2025

Abstract

The public release of ChatGPT in late 2022 has resulted in considerable publicity and has led to widespread discussion of the usefulness and capabilities of generative Artificial intelligence (Ai) language models. Its ability to extract and summarise data from textual sources and present [...] Read more.

The public release of ChatGPT in late 2022 has resulted in considerable publicity and has led to widespread discussion of the usefulness and capabilities of generative Artificial intelligence (Ai) language models. Its ability to extract and summarise data from textual sources and present them as human-like contextual responses makes it an eminently suitable tool to answer questions users might ask. Expanding on a previous analysis of the capabilities of ChatGPT3.5, this paper tested what archaeological literature appears to have been included in the training phase of three recent generative Ai language models: ChatGPT4o, ScholarGPT, and DeepSeek R1. While ChatGPT3.5 offered seemingly pertinent references, a large percentage proved to be fictitious. While the more recent model ScholarGPT, which is purportedly tailored towards academic needs, performed much better, it still offered a high rate of fictitious references compared to the general models ChatGPT4o and DeepSeek. Using ‘cloze’ analysis to make inferences on the sources ‘memorized’ by a generative Ai model, this paper was unable to prove that any of the four genAi models had perused the full texts of the genuine references. It can be shown that all references provided by ChatGPT and other OpenAi models, as well as DeepSeek, that were found to be genuine, have also been cited on Wikipedia pages. This strongly indicates that the source base for at least some, if not most, of the data is found in those pages and thus represents, at best, third-hand source material. This has significant implications in relation to the quality of the data available to generative Ai models to shape their answers. The implications of this are discussed. Full article

(This article belongs to the Special Issue AI in Open Access)

► Show Figures

Figure 1

24 pages, 9722 KiB

Open AccessArticle

Automation Applied to the Collection and Generation of Scientific Literature

by Nadia Paola Valadez-de la Paz, Jose Antonio Vazquez-Lopez, Aidee Hernandez-Lopez, Jaime Francisco Aviles-Viñas, Jose Luis Navarro-Gonzalez, Alfredo Valentin Reyes-Acosta and Ismael Lopez-Juarez

Publications 2025, 13(1), 11; https://doi.org/10.3390/publications13010011 - 6 Mar 2025

Abstract

Preliminary activities of searching and selecting relevant articles are crucial in scientific research to determine the state of the art (SOTA) and enhance overall outcomes. While there are automatic tools for keyword extraction, these algorithms are often computationally expensive, storage-intensive, and reliant on [...] Read more.

Preliminary activities of searching and selecting relevant articles are crucial in scientific research to determine the state of the art (SOTA) and enhance overall outcomes. While there are automatic tools for keyword extraction, these algorithms are often computationally expensive, storage-intensive, and reliant on institutional subscriptions for metadata retrieval. Most importantly, they still require manual selection of literature. This paper introduces a framework that automates keyword searching in article abstracts to help select relevant literature for the SOTA by identifying key terms matching that we, hereafter, call source words. A case study in the food and beverage industry is provided to demonstrate the algorithm’s application. In the study, five relevant knowledge areas were defined to guide literature selection. The database from scientific repositories was categorized using six classification rules based on impact factor (IF), Open Access (OA) status, and JCR journal ranking. This classification revealed the knowledge area with the highest presence and highlighted the effectiveness of the selection rules in identifying articles for the SOTA. The approach included a panel of experts who confirmed the algorithm’s effectiveness in identifying source words in high-quality articles. The algorithm’s performance was evaluated using the

F_{1}

Score, which reached 0.83 after filtering out non-relevant articles. This result validates the algorithm’s ability to extract significant source words and demonstrates its usefulness in building the SOTA by focusing on the most scientifically impactful articles. Full article

► Show Figures

Figure 1

29 pages, 3309 KiB

Open AccessArticle

Scientific Collaboration and Sustainable Development: A Bibliometric Analysis of the Andean Region, Panama, and Spain

by Gresky Gutiérrez-Sánchez, Patricio Álvarez-Muñoz, Purificación Galindo-Villardón and Purificación Vicente-Galindo

Publications 2025, 13(1), 10; https://doi.org/10.3390/publications13010010 - 27 Feb 2025

Cited by 1

Abstract

Background: Scientific collaboration has become a cornerstone of sustainable development, particularly in regions where research capacity and funding face significant challenges. The Andean region, Panama, and Spain offer a unique perspective due to their cultural and linguistic ties, alongside varying levels of scientific [...] Read more.

Background: Scientific collaboration has become a cornerstone of sustainable development, particularly in regions where research capacity and funding face significant challenges. The Andean region, Panama, and Spain offer a unique perspective due to their cultural and linguistic ties, alongside varying levels of scientific production and innovation. These disparities present opportunities for collaboration and targeted interventions to foster regional growth and contribute to global priorities. According to UNESCO, Latin America invests merely 0.56% of its GDP in research and development, underscoring the pressing need for innovative strategies to enhance scientific capacity and align efforts with the United Nations Sustainable Development Goals (SDGs). Methods: This study employed HJ-Biplot and MANOVA-Biplot methodologies to analyze bibliometric data across various thematic areas. These multivariate techniques offer a comprehensive exploration of the interrelationships between scientific production, research talent, and international collaboration, revealing significant patterns and associations. The data were sourced from the Scimago Iberoamerican platform, which aggregates information from Elsevier’s Scopus database on scientific journals and countries. The platform provides data in five-year increments, capturing trends in scientific output, international collaboration, and thematic focus across the Andean region, Panama, and Spain, spanning the period from 2012 to 2022. Results: The analysis identified significant correlations between scientific productivity, research talent, and international partnerships. Clustering disciplines such as engineering, computer science, and energy highlights the strong intersections between technology and economic development. The proximity of psychology and environmental sciences emphasizes the importance of social and environmental factors in scientific research. Conclusion: This study provides a comprehensive bibliometric analysis of the Andean region, Panama, and Spain, identifying critical drivers of scientific productivity and collaboration. The integration of advanced statistical methodologies reveals key associations between research talent, international partnerships, and thematic focus areas. While areas such as environmental sciences and biochemistry demonstrate alignment with innovation and sustainability goals, disciplines like engineering and mathematics require targeted investment to enhance their contributions. These findings underscore the importance of a balanced approach to research funding and policymaking to ensure equitable and impactful scientific development across regions. The results serve as a roadmap for fostering collaboration, strengthening leadership, and aligning research efforts with sustainable development objectives globally. Full article

► Show Figures

Figure 1

17 pages, 449 KiB

Open AccessArticle

Polarization in BRICS and G7: Scopus-Indexed Journal Production Trends (2013–2023)

by Eungi Kim, Sureshkrishnan Ramakrishnan and Jason Lim Chiu

Publications 2025, 13(1), 9; https://doi.org/10.3390/publications13010009 - 13 Feb 2025

Abstract

The objective of this study is to examine disparities in Scopus-indexed journal production between BRICS and G7 countries from 2013 to 2023, focusing on growth trends, open access (OA) and non-OA production, subject representation, and quality metrics. Using data from the SCImago Journal [...] Read more.

The objective of this study is to examine disparities in Scopus-indexed journal production between BRICS and G7 countries from 2013 to 2023, focusing on growth trends, open access (OA) and non-OA production, subject representation, and quality metrics. Using data from the SCImago Journal Rank portal, the analysis evaluated growth rates, quartile rankings, and publisher dynamics. G7 countries maintained their global leadership, characterized by stable production systems and high-impact journals predominantly managed by commercial publishers. In contrast, the countries of Brazil, Russia, India, China, and South Africa (BRICS) exhibited diverse trends: China and Russia demonstrated rapid expansion through state-backed initiatives and the rise of domestic publishers, aiming to reduce reliance on foreign publishers and enhance global visibility. However, India experienced a decline, while Brazil and South Africa showed only modest growth in Scopus-indexed journal production. Similarly, G7 countries displayed internal variability, with the UK and Italy achieving notable growth, whereas Japan and France faced declines. These disparities within both groups underscore the critical influence of national research policies and infrastructure on journal production. BRICS countries showed a strong focus on STEM disciplines, with China emerging as a leader in both OA and non-OA journal production. Conversely, G7 countries maintained a balanced representation across STEM and social sciences. These findings suggest that national policies and infrastructure investments are key drivers of journal production growth, with BRICS countries leveraging new initiatives for expansion and G7 countries maintaining dominance through established systems. Full article

(This article belongs to the Special Issue Bias in Indexing: Effects on Visibility and Equity)

► Show Figures

Figure 1

27 pages, 5423 KiB

Open AccessReview

Mapping the Conceptual Structure of University–Industry Knowledge Transfer: A Co-Word Analysis

by Vladimir Alfonso Ballesteros-Ballesteros and Rodrigo Arturo Zárate-Torres

Publications 2025, 13(1), 8; https://doi.org/10.3390/publications13010008 - 12 Feb 2025

Abstract

University–industry (U–I) collaborations are widely recognized as key drivers of economic progress, innovation, and competitiveness, fostering significant scholarly interest. Concurrently, research findings on these interactions have contributed to the establishment of an interdisciplinary field marked by the inherent complexity of these relationships. This [...] Read more.

University–industry (U–I) collaborations are widely recognized as key drivers of economic progress, innovation, and competitiveness, fostering significant scholarly interest. Concurrently, research findings on these interactions have contributed to the establishment of an interdisciplinary field marked by the inherent complexity of these relationships. This study aims to map the conceptual structure of university–industry knowledge transfer (UIKT) research from 1980 to 2023 by employing co-word analysis and social network analysis based on data retrieved from the Scopus database. The results reveal that 1577 documents were published during this period, incorporating 147 keywords, with the five most frequent being “innovation”, “higher education”, “university”, “technology transfer”, and “knowledge management”. The United Kingdom was identified as the most prolific country, contributing 366 documents, while Research Policy emerged as the most cited journal, with 3546 citations. This study offers a comprehensive overview of the current state of UIKT research, paving the way for future studies and providing valuable directions for further investigations. Full article

► Show Figures

Figure 1

11 pages, 2284 KiB

Open AccessReview

Meta-Research in Biomedical Investigation: Gaps and Opportunities Based on Meta-Research Publications and Global Indicators in Health, Science, and Human Development

by Ivan David Lozada-Martinez, David A. Hernandez-Paz, Ornella Fiorillo-Moreno, Yelson Alejandro Picón-Jaimes and Valmore Bermúdez

Publications 2025, 13(1), 7; https://doi.org/10.3390/publications13010007 - 10 Feb 2025

Abstract

Meta-research in biomedical science is crucial for ensuring rigour, relevance, and transparency in an era marked by the exponential growth of scientific publications. This study examines global and historical trends in meta-research activities within biomedicine and investigates their relationship with health, science, and [...] Read more.

Meta-research in biomedical science is crucial for ensuring rigour, relevance, and transparency in an era marked by the exponential growth of scientific publications. This study examines global and historical trends in meta-research activities within biomedicine and investigates their relationship with health, science, and human development indicators. A systematic analysis of 9633 publications from Scopus, Web of Science, and PubMed was conducted, focusing on publication volume, citation impact, and geographic distribution. Regression analyses reveal a significant positive association between meta-research activity and the Human Development Index (HDI), suggesting that meta-research contributes to societal advancement by enhancing evidence-based decision-making in health. However, no association was found between meta-research output and research and development (R&D) expenditure, reflecting the minimal resource requirements of secondary data-driven studies compared to primary or experimental research. Meta-research activity correlates positively with clinical trial completion, indicating its role in refining study designs and addressing evidence gaps. These findings highlight the importance of expanding meta-research in underrepresented regions to promote equity in scientific advancement and improve the reliability of biomedical knowledge. This result underscores the need for targeted support for meta-research, particularly in low- and middle-income countries with limited scientific infrastructure and resources for new knowledge generation. Full article

► Show Figures

Figure 1

17 pages, 1917 KiB

Open AccessArticle

Forecasting the Scientific Production Volumes of G7 and BRICS Countries in a Comparative Analysis

by Tindaro Cicero

Publications 2025, 13(1), 6; https://doi.org/10.3390/publications13010006 - 7 Feb 2025

Abstract

This study applies ARIMA models to forecast scientific production trends among G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) and BRICS (Brazil, Russia, India, China, and South Africa) countries using Scopus data from 1996 to 2023. The analysis [...] Read more.

This study applies ARIMA models to forecast scientific production trends among G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) and BRICS (Brazil, Russia, India, China, and South Africa) countries using Scopus data from 1996 to 2023. The analysis shows that G7 countries maintain steady growth driven by established research infrastructures, while BRICS nations, particularly China, display accelerated growth due to substantial investments in R&D. The forecasts indicate that China could reach over 2,000,000 indexed scientific publications annually by 2030, potentially reshaping the global research landscape. These findings provide valuable insights for policymakers and research institutions, highlighting the shifting dynamics of global scientific leadership and emphasizing the importance of sustained investment in research to remain competitive. Full article

► Show Figures

Figure 1

20 pages, 506 KiB

Open AccessArticle

Social Media Analysis of High-Impact Information and Communication Journals: Adoption, Use, and Content Curation

by Jesús Cascón-Katchadourian, Javier Guallar and Wileidys Artigas

Publications 2025, 13(1), 5; https://doi.org/10.3390/publications13010005 - 17 Jan 2025

Abstract

The use of social media to disseminate academic content is increasing, particularly in scientific journals. This study has the following two main objectives: first, exploring the use of social media by high-impact academic journals in two different SJR categories (Library and Information Sciences [...] Read more.

The use of social media to disseminate academic content is increasing, particularly in scientific journals. This study has the following two main objectives: first, exploring the use of social media by high-impact academic journals in two different SJR categories (Library and Information Sciences and Communication), and second, analyzing content curation carried out by the world’s most influential journals in both areas. The research methodology is descriptive with a quantitative approach regarding the items studied. The study finds that COM journals have a stronger social media presence than LIS journals, and X dominates in both categories and regions as the top social network, with significant influence as the only platform. On the other hand, content curation was found to a high degree in both areas, especially in the LIS area, with 93% vs. 80% in COM. The study highlights that both COM and LIS journals primarily focus on promoting recent articles, with COM diversifying content more than LIS. In terms of the content curation techniques used in both areas, the majority are abstracting and summarizing. Full article

► Show Figures

Figure 1

9 pages, 606 KiB

Open AccessArticle

Analyzing the Drivers Behind Retractions in Tuberculosis Research

by Franko O. Garcia-Solorzano, Shirley M. De la Cruz Anticona, Mario Pezua-Espinoza, Fernando A. Chuquispuma Jesus, Karen D. Sanabria-Pinilla, Christopher Chavez Veliz, Vladimir A. Huayta-Alarcón, Percy Mayta-Tristan and Leonid Lecca

Publications 2025, 13(1), 4; https://doi.org/10.3390/publications13010004 - 14 Jan 2025

Abstract

Tuberculosis research plays a crucial role in understanding and responding to the necessities of people with this disease, yet the integrity of this research is compromised by frequent retractions. Identifying and analyzing the main reasons for retraction of tuberculosis articles is essential for [...] Read more.

Tuberculosis research plays a crucial role in understanding and responding to the necessities of people with this disease, yet the integrity of this research is compromised by frequent retractions. Identifying and analyzing the main reasons for retraction of tuberculosis articles is essential for improving research practices and ensuring reliable scientific output. In this study, we conducted an advanced systematic literature review of retracted original articles on Tuberculosis, utilizing databases such as Web of Science, Embase, Scopus, PubMed, LILACS, and the Retraction Watch Database webpage. We found that falsification and plagiarism were the most frequent reasons for retraction, although 16% of the retracted articles did not declare the drivers behind the retraction. Almost half of the retracted studies received external funding, affecting not only those specific studies but future funding opportunities for this research field. Stronger measures of research integrity are needed to prevent misconduct in this vulnerable population. Full article

► Show Figures

Figure 1

8 pages, 591 KiB

Open AccessOpinion

Output-Normalized Score (OnS) for Ranking Researchers Based on Number of Publications, Citations, Coauthors, and Author Position

by Antonije Onjia

Publications 2025, 13(1), 3; https://doi.org/10.3390/publications13010003 - 4 Jan 2025

Abstract

This article discusses current methods for ranking researchers and proposes a new metric, the output-normalized score (OnS), which considers the number of publications, citations, coauthors, and the author’s position within each publication. The proposed OnS offers a balanced approach to evaluating a researcher’s [...] Read more.

This article discusses current methods for ranking researchers and proposes a new metric, the output-normalized score (OnS), which considers the number of publications, citations, coauthors, and the author’s position within each publication. The proposed OnS offers a balanced approach to evaluating a researcher’s scientific contributions while addressing the limitations of widely used metrics such as the h-index and its modifications. It favors publications with fewer coauthors while giving significant weight to both the author’s position in the publication and the total number of citations. Full article

► Show Figures

Figure 1

12 pages, 888 KiB

Open AccessArticle

Practicing Meta-Analytics with Rectification

by Ramalingam Shanmugam and Karan P. Singh

Publications 2025, 13(1), 2; https://doi.org/10.3390/publications13010002 - 2 Jan 2025

Abstract

This article demonstrates the necessity of assessing homogeneity in meta-analyses using the Higgins method. The researchers realize the importance of assessing homogeneity in meta-analytic work. However, a significant issue with the Higgins method has been identified. In this article, we explain the nature [...] Read more.

This article demonstrates the necessity of assessing homogeneity in meta-analyses using the Higgins method. The researchers realize the importance of assessing homogeneity in meta-analytic work. However, a significant issue with the Higgins method has been identified. In this article, we explain the nature of this problem and propose solutions to address it. Our narrative in this article is to point out the problem, analyze it, and present it well. A prerequisite to check the consistency of findings in comparable studies in meta-analyses is that the studies should be homogeneous, not heterogeneous. The Higgins

I^{2}

score, a version of the Cochran Q value, is commonly used to assess heterogeneity. The Higgins score is an improvement in the Q value. However, there is a problem with Higgins score statistically. The Higgins score is supposed to follow a Chi-squared distribution, but it does not do so because the Chi-squared distribution becomes invalid once the Q score is less than the degrees of freedom. This problem was recently rectified using an alternative method (

S^{2}

score). Using this method, we examined 14 published articles representing 133 datasets and observed that many studies declared homogeneous by the Higgins method were, in fact, heterogeneous. This article urges the research community to be cautious in making inferences using the Higgins method. Full article

► Show Figures

Figure 1

11 pages, 235 KiB

Open AccessOpinion

Exploring the Need to Use “Plagiarism” Detection Software Rationally

by Petar Milovanovic, Tatjana Pekmezovic and Marija Djuric

Publications 2025, 13(1), 1; https://doi.org/10.3390/publications13010001 - 2 Jan 2025

Abstract

Universities and journals increasingly rely on software tools for detecting textual overlap of a scientific text with the previously published literature to detect potential plagiarism. Although software outputs need to be carefully reviewed by competent humans to verify the existence of plagiarism, university [...] Read more.

Universities and journals increasingly rely on software tools for detecting textual overlap of a scientific text with the previously published literature to detect potential plagiarism. Although software outputs need to be carefully reviewed by competent humans to verify the existence of plagiarism, university and journal staff, for various reasons, often erroneously interpret the degree of plagiarism based on the percentage of textual overlap shown in the similarity report. This is often accompanied by explicit recommendations to the author(s) to paraphrase the text to achieve an “acceptable” percentage of overlap. Here, based on the available literature and real-world examples from similarity reports, we provide a classification with extensive examples of phrases that falsely inflate the similarity index and argue the futility and dangers of rephrasing such statements just for the sake of reducing the similarity index. The examples provided in this paper call for a more reasonable assessment of text similarity. To fully endorse the principles of academic integrity and prevent loss of clarity of the scientific literature, we believe it is important to shift from pure bureaucratic and quantificational view on the originality of scientific texts to human-centered qualitative assessment of the manuscripts, including the software outputs. Full article

Journal Description

Publications

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Further Information

Guidelines

MDPI Initiatives

Follow MDPI