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The aim of this study was to perform a bibliometric analysis to discover what topics of dental YouTube videos have been investigated by the scientific literature, and evaluate how video characteristics were related to citation count. The Scopus electronic literature database was accessed to identify relevant papers. After screening, a total of 128 papers entered the analysis. The bibliographic data were provided by Scopus, whereas content evaluations were manually performed. Most papers evaluated videos recorded in English (85.9%). Each of the 128 papers analyzed a mean (±SD) of 79.2 ± 61.6 videos. Mean journal impact factor was 1.8 ± 1.4, and mean citation count was 13.0 ± 22.4. The preference for publication of papers was inclined towards dental journals (80.5%), with the majority (54.7%) being published without open access. Papers dealing with videos targeting patients/public had higher citations than those targeting dental professionals only (14.1 ± 23.4 vs. 4.0 ± 6.3, p < 0.001). The most represented as well as the most highly cited specialty of the dental YouTube publications was oral and maxillofacial surgery/oral medicine. Some twin or triplet studies published in the same year covering the same topic were identified, but they often covered a different number of videos. [ABSTRACT FROM AUTHOR]

Background: Natural language processing, such as ChatGPT, demonstrates growing potential across numerous research scenarios, also raising interest in its applications in public health and epidemiology. Here, we applied a bibliometric analysis for a systematic assessment of the current literature related to the applications of ChatGPT in epidemiology and public health. Methods: A bibliometric analysis was conducted on the Biblioshiny web-app, by collecting original articles indexed in the Scopus database between 2010 and 2023. Results: On a total of 3431 original medical articles, "Article" and "Conference paper", mostly constituting the total of retrieved documents, highlighting that the term "ChatGPT" becomes an interesting topic from 2023. The annual publications escalated from 39 in 2010 to 719 in 2023, with an average annual growth rate of 25.1%. In terms of country production over time, the USA led with the highest overall production from 2010 to 2023. Concerning citations, the most frequently cited countries were the USA, UK, and China. Interestingly, Harvard Medical School emerges as the leading contributor, accounting for 18% of all articles among the top ten affiliations. Conclusions: Our study provides an overall examination of the existing research interest in ChatGPT's applications for public health by outlining pivotal themes and uncovering emerging trends. [ABSTRACT FROM AUTHOR]

This study investigates the coevolution of coauthorship and citation networks and their influence on scientific metrics such as the h-index and journal impact factors. Using a preferential attachment mechanism, we developed a model that integrated these networks and validated it with data from the American Physical Society (APS). While the correlations between reference counts, paper lifetime, and team sizes with scientific impact metrics are well-known, our findings demonstrate how these relationships vary depending on specific model parameters. For instance, increasing reference counts or reducing paper lifetime significantly boosts both journal impact factors and h-indexes, while expanding team sizes without adding new authors can artificially inflate h-indexes. These results highlight potential vulnerabilities in commonly used metrics and emphasize the value of modeling and simulation for improving bibliometric evaluations. [ABSTRACT FROM AUTHOR]

This paper provides a bibliometric analysis of current research trends in the field of artificial intelligence (AI), focusing on key topics such as deep learning, machine learning, and security in AI. Through the lens of bibliometric analysis, we explore publications published from 2020 to 2024, using primary data from the Clarivate Analytics Web of Science Core Collection. The analysis includes the distribution of studies by year, the number of studies and citation rankings in journals, and the identification of leading countries, institutions, and authors in the field of AI research. Additionally, we investigate the distribution of studies by Web of Science categories, authors, affiliations, publication years, countries/regions, publishers, research areas, and citations per year. Key findings indicate a continued growth of interest in topics such as deep learning, machine learning, and security in AI over the past few years. We also identify leading countries and institutions active in researching this area. Awareness of data security is essential for the responsible application of AI technologies. Robust security frameworks are important to mitigate risks associated with AI integration into critical infrastructure such as healthcare and finance. Ensuring the integrity and confidentiality of data managed by AI systems is not only a technical challenge but also a societal necessity, demanding interdisciplinary collaboration and policy development. This analysis provides a deeper understanding of the current state of research in the field of AI and identifies key areas for further research and innovation. Furthermore, these findings may be valuable to practitioners and decision-makers seeking to understand current trends and innovations in AI to enhance their business processes and practices. [ABSTRACT FROM AUTHOR]

Craft beer represents a dynamic and creative segment within the food and beverage industry, emphasizing quality, aroma, health, sustainability, locality, and tailored brewing techniques. This paper explores the multifaceted roles of craft beer's production and consumption growth dynamics. Both a bibliometric analysis and a systematic literature review were conducted on a sample of 239 scientific papers to provide an in-depth evaluation of the main characteristics and influences that craft beer has in the field of food science. Based on the identified roles of craft beer/breweries in the selected sample of literature, a conceptual framework was constructed to serve as a guideline for policymakers and different stakeholders. In this way, our findings enrich the existing literature and contribute to a better understanding of craft beer production and surroundings, which can be beneficial for promoting sustainable policies and innovative strategies for the growth of small/micro-producers and entrepreneurs in this niche market. Furthermore, this evidence can stimulate clear and ethical information to enhance consumers' knowledge and agendas to strengthen the identity of local communities. [ABSTRACT FROM AUTHOR]

Research on forest carbon storage (FCS) is crucial for the sustainable development of human society given the context of global climate change. Previous FCS studies formed the science base of the FCS field but lacked a macrolevel knowledge summary. This study combined the scientometric mapping tool VOSviewer and multiple statistical models to conduct a comprehensive knowledge graph mining and analysis of global FCS papers (covering 101 countries, 1712 institutions, 5435 authors, and 276 journals) in the Web of Science database as of 2022, focusing on revealing the macro spatiotemporal pattern, multidimensional research status, and topic evolution process of FCS research at the global scale, so as to grasp the status of global FCS research more clearly and comprehensively, thereby facilitating the future decision-making and practice of researchers. The results showed the following: (1) In the past three decades, the number of FCS papers indicated an increasing trend, with a growth rate of 4.66/yr, particularly significant after 2010. These papers were mainly from Europe, the Americas, and Asia, while there was a huge gap between Africa, Oceania, and the above regions. (2) For the research status at the national, institutional, scholar, and journal levels, the USA, with 331 FCS papers and 18,653 total citations, was the most active and influential country in global FCS research; the United States Forest Service topped the influential ranking with 4115 citations; Grant M. Domke and Jerome Chave were the most active and influential FCS researchers globally, respectively. China's activity (237 papers) and influence (5403 citations) ranked second, and the Chinese Academy of Sciences was the most active research institution in the world. Currently, FCS research is published in a growing number of journals, among which Forest Ecology and Management ranked first in the number of papers (154 papers) and citations (6374 citations). (3) In recent years, the keyword frequency of monitoring methods, driving factors, and reasonable management for FCS has increased rapidly, and many new related keywords have emerged, which means that researchers are not only focusing on the estimation and monitoring of FCS but also increasingly concerned about its driving mechanism and sustainable development. [ABSTRACT FROM AUTHOR]

In recent years, neutrosophic theory has garnered increasing attention within scholarly circles due to its applicability in various domains. Within these domains, the field of decision-making has derived significant advantages from the progressions in neutrosophic theory. Notably, neutrosophic theory has made substantial contributions by advancing and offering a range of aggregation operators and information measures specifically designed for enhancing decision-making processes. In this context, this study aims to conduct a comprehensive bibliometric analysis of the current research landscape in the field of neutrosophic theory, with a specific focus on understanding its applications and development trends. Our analysis reveals that the scientific literature addresses neutrosophic theory in a diverse range of applications. This examination encompasses a scrutiny of key contributors, affiliated academic institutions, influential publications, and noteworthy journals within the neutrosophic domain. To achieve this, we have curated a dataset comprising scholarly papers retrieved from Clarivate Analytics' Web of Science Core Collection database, employing keywords closely aligned with neutrosophic theory and its applications, spanning a specified timeframe starting from the year in which the first paper on neutrosophic theory was published, namely, from 2005 until 2022. Our findings underscore sustained and robust scholarly interest in neutrosophic theory, characterized by a considerable high annual growth rate of 43.74% during the specified period. Additionally, our investigation delves into the identification and analysis of pivotal keywords and emerging trends, shedding light on prominent research trajectories within this domain. Furthermore, we elucidate collaborative networks among authors, their academic affiliations, and the global distribution across diverse countries and territories, providing valuable insights into the worldwide proliferation of neutrosophic research and applications. Employing n-gram analysis techniques across titles, keywords, abstracts, and keyword-plus fields unveils a multitude of applications where neutrosophic theory plays a central role. The analysis culminates in a review of globally cited documents and a comprehensive discussion highlighting the significance of neutrosophic theory in contemporary research and problem-solving contexts. [ABSTRACT FROM AUTHOR]

Background: Pediatric dentistry shares many skills with pediatrics. This review evaluates the amount of literature on pediatric dentistry in the first 30 pediatric journals classified by the Web of Science in 2019. The aim was to perform a quantitative analysis of the main dental topics addressed. Methods: A scoping review with the PRISMA-ScR criteria was performed. The Clarivate Analytics Journal Citation Report was consulted for journals ranked in the category “Pediatrics” in 2019. Papers were searched in PubMed using an ad hoc prepared string. Results: A total of 504 papers were included. Papers on dental hard tissues were the most prevalent (45.6%), followed by dental public health (23.2%), orofacial development (15.3%), soft tissues related conditions (12.3%), and orofacial trauma (3.6%). Increasing trends have been observed for total papers published (R ² = 0.9822) and total dental papers (R² = 0.8862), with no statistically significant differences (χ 2 (6) = 0.051 p > 0.05). The majority of papers (n = 292, 57.9%) were cited between 1 and 10 times, whilst less than 7% of papers received more than 40 citations. Discussion: It is desirable that papers on pediatric dentistry increase in the pediatric scenario, allowing the two related disciplines to intertwine more in the future. [ABSTRACT FROM AUTHOR]

Wildfires are a critical driver of landscape transformation on Earth, representing a dynamic and ephemeral process that poses challenges for accurate early detection. To address this challenge, researchers have increasingly turned to deep learning techniques, which have demonstrated remarkable potential in enhancing the performance of wildfire detection systems. This paper provides a comprehensive review of fire detection using deep learning, spanning from 1990 to 2023. This study employed a comprehensive approach, combining bibliometric analysis, qualitative and quantitative methods, and systematic review techniques to examine the advancements in fire detection using deep learning in remote sensing. It unveils key trends in publication patterns, author collaborations, and thematic focuses, emphasizing the remarkable growth in fire detection using deep learning in remote sensing (FDDL) research, especially from the 2010s onward, fueled by advancements in computational power and remote sensing technologies. The review identifies "Remote Sensing" as the primary platform for FDDL research dissemination and highlights the field's collaborative nature, with an average of 5.02 authors per paper. The co-occurrence network analysis reveals diverse research themes, spanning technical approaches and practical applications, with significant contributions from China, the United States, South Korea, Brazil, and Australia. Highly cited papers are explored, revealing their substantial influence on the field's research focus. The analysis underscores the practical implications of integrating high-quality input data and advanced deep-learning techniques with remote sensing for effective fire detection. It provides actionable recommendations for future research, emphasizing interdisciplinary and international collaboration to propel FDDL technologies and applications. The study's conclusions highlight the growing significance of FDDL technologies and the necessity for ongoing advancements in computational and remote sensing methodologies. The practical takeaway is clear: future research should prioritize enhancing the synergy between deep learning techniques and remote sensing technologies to develop more efficient and accurate fire detection systems, ultimately fostering groundbreaking innovations. [ABSTRACT FROM AUTHOR]

Confronted with the significant challenges of global climate change and environmental deterioration, the pursuit of carbon emission peaks and the realization of carbon neutrality have become a collective goal for countries worldwide. As an exemplary combustion technology noted for its efficiency and environmental friendliness, the circulating fluidized bed (CFB) is instrumental in curbing the release of carbon dioxide alongside other deleterious gases. The technology is pivotal in promoting the clean and efficient use of coal, simultaneously expediting the global shift towards a sustainable, green, and low-carbon future. This study employs a bibliometric analysis, a social network analysis, and information visualization techniques to delve into the evolution of CFB technology, leveraging the Web of Science database (SCI-EXPANDED and CPCI-S) and the Derwent Innovations Index (DII). Through a meticulous examination of academic papers and patent literature related to CFB technology, this research unveils the developmental trajectory and trends of CFB technology, providing a scientific foundation and reference for strategic technology planning and focused research in key areas. The findings indicate that, while there is a downward trend in the global publication of academic papers on CFB technology, the number of patent applications continues to grow steadily. CFB technology has achieved significant advancements in enhancing combustion efficiency, environmental protection, energy utilization, and waste management, and is progressing towards a direction of diversification and greater efficiency. Moving forward, the development of CFB technology should concentrate on pivotal areas such as material science, fluid dynamics simulation, environmental impact assessment, system integration, and intelligentization, to foster ongoing innovation and a broad application of the technology. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the 50 most cited articles on shoulder arthroplasty (SA) and their characteristics. The Thomson ISIWeb of Science was searched with the following search terms: "shoulder arthroplasty", "shoulder replacement", "shoulder prosthesis" and "shoulder implant". All papers dealing with SA, including its perioperative and postoperative management, were included in this study. Citations ranged from 797 to 52 for the 50 highest cited papers on SA. According to absolute numbers, the top 10 papers were cited at least 118 times. Overall, 78% (n = 43) were clinical and the remaining articles were basic science research (one anatomic, six biomechanical). The most prevalent level of evidence was IV (72%). The Journal of Shoulder and Elbow Surgery published 40% of the studies. The majority of studies were conducted in the United States and eight other countries. The publication years of the most-cited articles ranged from 1991 to 2020, with the 2000s accounting for the most articles (96%) and the period from 2006 to 2010 with the absolute largest number of articles (17). This article provides a building block in the SA surgery. [ABSTRACT FROM AUTHOR]

Over the last decade, there has been a large amount of research on technology-enhanced learning (TEL), including the exploration of sensor-based technologies. This research area has seen significant contributions from various conferences, including the European Conference on Technology-Enhanced Learning (EC-TEL). In this research, we present a comprehensive analysis that aims to identify and understand the evolving topics in the TEL area and their implications in defining the future of education. To achieve this, we use a novel methodology that combines a text-analytics-driven topic analysis and a social network analysis following an open science approach. We collected a comprehensive corpus of 477 papers from the last decade of the EC-TEL conference (including full and short papers), parsed them automatically, and used the extracted text to find the main topics and collaborative networks across papers. Our analysis focused on the following three main objectives: (1) Discovering the main topics of the conference based on paper keywords and topic modeling using the full text of the manuscripts. (2) Discovering the evolution of said topics over the last ten years of the conference. (3) Discovering how papers and authors from the conference have interacted over the years from a network perspective. Specifically, we used Python and PdfToText library to parse and extract the text and author keywords from the corpus. Moreover, we employed Gensim library Latent Dirichlet Allocation (LDA) topic modeling to discover the primary topics from the last decade. Finally, Gephi and Networkx libraries were used to create co-authorship and citation networks. Our findings provide valuable insights into the latest trends and developments in educational technology, underlining the critical role of sensor-driven technologies in leading innovation and shaping the future of this area. [ABSTRACT FROM AUTHOR]

Biodiesel can be produced from vegetable oils, animal fats, frying oils, and from microorganism-synthesized oils. These sources render biodiesel an easily biodegradable fuel. The aim of this work was to perform an advanced bibliometric analysis of primary studies relating to biodiesel production worldwide by identifying the key countries and regions that have shown a strong engagement in this area, and by understanding the dynamics of their collaboration and research outputs. Additionally, an assessment of the main primary feedstocks employed in this research was carried out, along with an analysis of the current and future trends that are expected to define new paths and methodologies to be used in the manufacture of biodegradable and renewable fuels. A total of 4586 academic outputs were selected, including peer-reviewed research articles, conference papers, and literature reviews related to biodiesel production, in the time period spanning from 2010 to 2021. Articles that focused on feedstocks for the production of biodiesel were also included, with a search that returned 330 papers. Lastly, 60 articles relating to biodiesel production via sewage were specifically included to allow for an analysis of this source as a promising feedstock in the future of the biofuel market. Via the geocoding and the document analyses performed, we concluded that China, Malaysia, and India are the largest writers of articles in this area, revealing a great interest in biofuels in Asia. Additionally, it was noted that environmental concerns have caused authors to conduct research on feedstocks that can address the sustainability challenges in the production of biodiesel. [ABSTRACT FROM AUTHOR]

The eddy current brake (ECB) is a braking technology that continues to be developed. The use of the ECB has excellent potential to be applied to vehicles. Various studies have proposed the design, characteristics, and advantages of each. However, further analysis is needed to assess the performance of the ECB and what factors affect the performance. However, no studies have been found that discuss eddy current brakes using bibliometric analysis. Bibliometric analysis is a method used for mapping and knowledge of existing gaps in a particular topic. This article aims to provide a complete discussion with bibliometric statistical methods that have never been presented before in the field of eddy current brakes, especially the phenomenon of heat generation. In addition, the prediction of research gaps in this field can be identified as the initial results of further research. The analysis was carried out using VOSviewer and Biblioshiny integrated through the RStudio tool. The data are obtained through the Scopus database, which is then exported in CSV form. Obtaining the data depends on the keywords used. In this case, the obtained document is filtered with the features provided by Scopus. From the analysis conducted, it was found that the topic related to heat in eddy current brakes is still a recent discussion. Discussions on the heat increase in the ECB are still limited and require mapping and analysis of what parts still need development. The phenomenon of heat generation is one novelty that allows it to be researched. One example from the scientific data obtained is that there are 207 documents in the form of articles and conference papers with a total of 533 authors. [ABSTRACT FROM AUTHOR]

Since ancient times, people have used salt for cooking and preserving food, its healing benefits, and as a means of payment. Therefore, the first settlements were located near water, food, and preferably salt, as prerequisites to further social and economic development. Naturally, the social development, the healing properties of salt, and the beauty of some salt landscapes have led to the development of tourism as an essential asset for rural communities. This paper aims to investigate the research focusing on the use of salt resources in tourism and to see if the exploitation of salt landscapes is an actual research topic linked to rural development. The study's primary objectives are to investigate the scientific output in the tourism field, the main drivers in scientific production, and any connection between the importance of salt landscapes in tourism and sustainable rural development. The article represents a bibliometric analysis of 437 scientific articles published in prestigious journals indexed in the Web of Science until November 2023. The results emphasised a need for more research on using salt landscapes and resources in tourism as a central topic, as most identified studies focus on proposing models for the sustainable development of former salt mines and ecosystem restoration using tourism activity. Since many salt mining operations have been closed and the inhabitants of the neighbouring rural localities have been left without the related income, the results of this research are helpful for specialists in the field and for decision-makers to have a clear view of the development trends of areas rich in salt resources for tourism purposes. [ABSTRACT FROM AUTHOR]

As voice user interfaces (VUIs) rapidly transform the landscape of human–computer interaction, their potential to revolutionize user engagement is becoming increasingly evident. This paper aims to advance the field of human–computer interaction by conducting a bibliometric analysis of the user experience associated with VUIs. It proposes a classification framework comprising six research categories to systematically organize the existing literature, analyzes the primary research streams, and identifies future research directions within each category. This systematic literature review provides a comprehensive analysis of the development and effectiveness of VUIs in facilitating natural human–machine interaction. It offers critical insights into the user experience of VUIs, contributing to the refinement of VUI design to optimize overall user interaction and satisfaction. [ABSTRACT FROM AUTHOR]

Seed orchards are important seed resources for producing improved tree crops for future plantations, forest restoration, and forestry practices (i.e., gene conservation) and for transmitting current gene diversity to future generations. Seed orchards are a major sub-division in forest science. The establishment and management of a seed orchard involves many steps, from the selection of superior trees to the harvesting of a seed crop. Studying the trends and future directions of seed orchards using different analysis methods is critically important, especially to establish resistant forests via the production of climate-smart, biotic/abiotic-stress-resistant seedling materials. Published papers related to seed orchards should be analyzed to determine the current trends in this field and to contribute to its future directions. Bibliometric analysis has been used for different purposes in various scientific fields. However, it has not been performed for publications in seed orchards. This study was carried out to analyze the current trends of research on seed orchards and to determine the future directions of these orchards based on published papers. For these purposes, 1018 published papers were obtained from the Science Citation Index, Science Citation Index Expanded, and citation index databases of "Web of Science" using the keyword "seed orchard". The papers were published between 1980 and 2022 and were subjected to bibliometric analysis based on the most prolific contributors, references, countries, and keywords. CiteSpace software 6.1 R6 was applied to visualize information about seed orchard research. The average number of citations per publication was 13.05, and the 4 H-Index of the publication set was 48. The most prolific contributors with the strongest citation bursts, the highest centrality, and the greatest numbers of published papers were from Canada, Sweden, South Korea, Finland, and Czech Republic, while Canada (186 published articles), the USA (140), and Sweden (115), together with China, Brazil, and Germany, were active countries, especially based on citations from recent years. The "keywords" of the papers were the core of the research. "Mating pattern", "Swedish forestry", "fertility variation", "Hymenoscyphus fraxineus", "threatened Pacific sandalwood", "outbreeding depression", "climate change", "management", and "growth", together with others such as "genetic improvement" and "effective size", were active study areas and keywords, based on results of the analysis. They also guided the literature search and inventory and classification of early studies and served as predictors for future studies. The results of this study are discussed based on the trends and future directions of the research and development of seed orchards. [ABSTRACT FROM AUTHOR]

The global impact of the COVID-19 pandemic has been profound, placing significant challenges upon healthcare systems and the world economy. The pervasive presence of illness, uncertainty, and fear has markedly diminished overall life satisfaction. Consequently, sentiment analysis has gained substantial traction among scholars seeking to unravel the emotional and attitudinal dimensions of this crisis. This research endeavors to provide a bibliometric perspective, shedding light on the principal contributors to this emerging field. It seeks to spotlight the academic institutions associated with this research domain, along with identifying the most influential publications in terms of both paper volume and h-index metrics. To this end, we have meticulously curated a dataset comprising 646 papers sourced from the ISI Web of Science database, all centering on the theme of sentiment analysis during the COVID-19 pandemic. Our findings underscore a burgeoning interest exhibited by the academic community in this particular domain, evident in an astonishing annual growth rate of 153.49%. Furthermore, our analysis elucidates key keywords and collaborative networks within the authorship, offering valuable insights into the global proliferation of this thematic pursuit. In addition to this, our analysis encompasses an n-gram investigation across keywords, abstracts, titles, and keyword plus, complemented by an examination of the most frequently cited works. The results gleaned from these endeavors offer crucial perspectives, contribute to the identification of pertinent issues, and provide guidance for informed decision-making. [ABSTRACT FROM AUTHOR]

Spatial accessibility is an essential manifestation of social equity and spatial planning. However, when examining spatial accessibility, systematic review studies dominate the literature, with fewer studies employing evaluative and relational bibliometric approaches. Thus, to provide a comprehensive overview of spatial accessibility research from 1999 to 2022, the works of literature referenced and analyzed by the Web of Science during 1999–2022 were analyzed: bibliometrics and scientific mapping methods using R software, the biblioshiny web program, tidyverse (ggplot2), and VOSviewer. The analysis results indicate a significant increase in the number of research papers addressing spatial accessibility throughout the research period accompanied by a continuous expansion of the research area. Collaboration and research endeavors among countries in this domain have deepened, leading to a continual improvement in the quality of papers. In addition, influential journals, authors, and articles in the field of spatial accessibility were also counted. New data, methods, and technology will become substantially more critical in accessibility research. [ABSTRACT FROM AUTHOR]

This paper presents a bibliometric analysis within the research domain dedicated to the utilization of agent-based modeling (ABM) in the field of transportation. By employing specific keywords related to both agent-based modeling and transportation, we have identified and extracted 1016 scholarly papers from the ISI Web of Science database, spanning the period from 2002 to 2023. Through the application of bibliometric methods, we have systematically examined key contributors, affiliations of academic institutions, influential publications, and renowned journals within this domain. Our analysis reveals a consistent and robust growth in scholarly interest pertaining to agent-based modeling in the field of transportation throughout the considered period. Notably, within approximately four decades of ABM's application in transportation, a distinct upward trajectory began in 2008, culminating in the year 2021. The entire considered period witnessed a remarkable surge in paper production, characterized by an annual growth rate of 21.67%. Furthermore, employing an n-gram analysis, we have delineated and discussed the principal areas within transportation that have progressively benefited from the advancements in agent-based modeling. Prominently, the domains of air transport and road transport have exhibited substantial development over time, while the implications of climate change have emerged as a persistent concern throughout the entire study period. [ABSTRACT FROM AUTHOR]

Natural language processing (NLP) plays a pivotal role in modern life by enabling computers to comprehend, analyze, and respond to human language meaningfully, thereby offering exciting new opportunities. As social media platforms experience a surge in global usage, the imperative to capture and better understand the messages disseminated within these networks becomes increasingly crucial. Moreover, the occurrence of adverse events, such as the emergence of a pandemic or conflicts in various parts of the world, heightens social media users' inclinations towards these platforms. In this context, this paper aims to explore the scientific literature dedicated to the utilization of NLP in social media research, with the goal of highlighting trends, keywords, and collaborative networks within the authorship that contribute to the proliferation of papers in this field. To achieve this objective, we extracted and analyzed 1852 papers from the ISI Web of Science database. An initial observation reveals a remarkable annual growth rate of 62.18%, underscoring the heightened interest of the academic community in this domain. This paper includes an n-gram analysis and a review of the most cited papers in the extracted database, offering a comprehensive bibliometric analysis. The insights gained from these efforts provide essential perspectives and contribute to identifying pertinent issues in social media analysis addressed through the application of NLP. [ABSTRACT FROM AUTHOR]

In recent years, the domain of renewable energy communities has experienced dynamic growth, spurred by European Union (EU) legislation that became law for all 27 Member States in June 2021. This legislative framework intensified research efforts aimed at discovering new methods for sustainable energy sources through the development of individual and collective energy communities. Each EU country has implemented distinct frameworks for renewable energy communities, leading to varied legislative approaches. This has spurred exponential investment, facilitating the deployment of photovoltaic and battery energy storage systems, offering significant economic and environmental benefits to community members. Against this backdrop, the purpose of this analysis is to investigate academic publications related to renewable energy communities. Using a dataset extracted from the ISI Web of Science database, this study employs a bibliometric approach to identify the main authors, affiliations, and journals and analyze collaboration networks, as well as discern key topics and the countries involved. The analysis reveals an annual growth rate of 42.82%. Through thematic maps, WordClouds, three-field plots, and a review of the top 10 globally cited documents, this study provides a comprehensive perspective on the evolving domain of renewable energy communities. [ABSTRACT FROM AUTHOR]

Manganese (Mn) pollution poses a serious threat to the health of animals, plants, and humans. The microbial-mediated Mn(II) removal method has received widespread attention because of its rapid growth, high efficiency, and economy. Mn(II)-oxidizing bacteria can oxidize toxic soluble Mn(II) into non-toxic Mn(III/IV) oxides, which can further participate in the transformation of other heavy metals and organic pollutants, playing a crucial role in environmental remediation. This study aims to conduct a bibliometric analysis of research papers on bacterial Mn(II) oxidation using CiteSpace, and to explore the research hotspots and developmental trends within this field between 2008 and 2023. A series of visualized knowledge map analyses were conducted with 469 screened SCI research papers regarding annual publication quantity, author groups and their countries and regions, journal categories, publishing institutions, and keywords. China, the USA, and Japan published the most significant number of research papers on the research of bacterial Mn(II) oxidation. Research hotspots of bacterial Mn(II) oxidation mainly focused on the species and distributions of Mn(II)-oxidizing bacteria, the influencing factors of Mn(II) oxidation, the mechanisms of Mn(II) oxidation, and their applications in environment. This bibliometric analysis provides a comprehensive visualized knowledge map to quickly understand the current advancements, research hotspots, and academic frontiers in bacterial Mn(II) oxidation. [ABSTRACT FROM AUTHOR]

In the continuously evolving field of E-government, understanding the breadth and depth of academic research is crucial for advancing governmental digital transformation and policy development. This study employs visual bibliometric analysis, using the Web of Science database to map the evolution trajectory of E-government research from 2000 to 2023. By utilizing CiteSpace for a comprehensive examination of 4536 academic articles, this paper outlines the growth patterns and thematic evolution within the field. The development of the E-government field is delineated into four distinct phases: the budding period (2000–2003), the bottleneck period (2004–2014), the development period (2015–2018), and the growth period (2019–2023), which are each marked by unique thematic shifts and technological advancements. The research results reveal the transformation of research focus in different periods, from the initial focus on the technological means and the electronic transformation of government services, moving on to more complex issues such as E-government acceptance and government transparency and corruption, and ultimately to the current focus on innovation and smart cities. In addition, the paper also clarifies that the research boom that began in 2019 is driven by technological innovation opportunities, the improvement in infrastructure, and multidisciplinary research. By depicting these developmental stages and emerging trends, this study not only unveils past academic efforts but also forecasts future research directions, thereby providing valuable insights for researchers and policymakers aiming to understand and implement effective E-government strategies. [ABSTRACT FROM AUTHOR]

In recent years, the research community has increasingly embraced topics related to smart cities, recognizing their potential to enhance residents' quality of life and create sustainable, efficient urban environments through the integration of diverse systems and services. Concurrently, recommender systems have demonstrated continued improvement in accuracy, delivering more precise recommendations for items or content and aiding users in decision-making processes. This paper explores the utilization of recommender systems in the context of smart cities by analyzing a dataset comprised of papers indexed in the ISI Web of Science database. Through bibliometric analysis, key themes, trends, prominent authors and institutions, preferred journals, and collaboration networks among authors were extracted. The findings revealed an average annual scientific production growth of 25.85%. Additionally, an n-gram analysis across keywords, abstracts, titles, and keywords plus, along with a review of selected papers, enriched the analysis. The insights gained from these efforts offer valuable perspectives, contribute to identifying pertinent issues, and provide guidance on trends in this evolving field. The importance of recommender systems in the context of smart cities lies in their ability to enhance urban living by providing personalized and efficient recommendations, optimizing resource utilization, improving decision-making processes, and ultimately contributing to a more sustainable and intelligent urban environment. [ABSTRACT FROM AUTHOR]

With the rapid growth in urban construction in Malaysia, road breakage has challenged traditional manual inspection methods. In order to quickly and accurately detect the extent of road breakage, it is crucial to apply automated road crack detection techniques. Researchers have long studied image-based road crack detection techniques, especially the deep learning methods that have emerged in recent years, leading to breakthrough developments in the field. However, many issues remain in road crack detection methods using deep learning techniques. The field lacks state-of-the-art systematic reviews that can scientifically and effectively analyze existing works, document research trends, summarize outstanding research results, and identify remaining shortcomings. To conduct a systematic review of the relevant literature, a bibliometric analysis and a critical analysis of the papers published in the field were performed. VOSviewer and CiteSpace text mining tools were used to analyze and visualize the bibliometric analysis of some parameters derived from the articles. The history and current status of research in the field by authors from all over the world are elucidated and future trends are analyzed. [ABSTRACT FROM AUTHOR]

This paper presents an author co-citation analysis of the research on L2 vocabulary acquisition that was published in the 2020 calendar year. The most significant influence at this time is Paul Nation—cited in 85% of the publication set—but a number of other important influences can also be identified, notably, Laufer, Hulstijn, Schmitt and Webb. This paper draws some comparisons with data from 1990, and speculates on how "research fronts" might be identified in an author co-citation data set. [ABSTRACT FROM AUTHOR]

The world is accelerating globalization and urbanization; thus, planning plays an irreplaceable role in the macro development, especially in sustainable development. Planning research is important in turning theories of planning into urban practices. This research based on the theory that planning research is crucial, as it represents that planning-related activities improve processes in urbanization. However, the current understanding of the importance of planning research is limited. There is no research on the interaction between planning research and macro national development to support the importance of planning or its research. This study uses 750,000 articles on urban planning fields from WoS from 1950 to the present. Firstly, the study concludes the investment pattern changes of the global planning research. Over the past 70 years, the total number and diversity of countries engaged in planning research have grown rapidly, and developing countries have gradually integrated into the mainstream research community and become the main contributors. Secondly, the investment intensity and characteristics of planning research are consistent with the speed and characteristics of urbanization, which proves that to some extent, the demand of urbanization development drives the investment of planning research. Then, according to the different characteristics of planning research investment in different countries, this paper summarizes the main investment characteristics of major countries, analyzes the development rule behind the investment characteristics, and predicts the interaction with the international political and economic pattern. By analyzing the relationship between planning research intensity and urbanization, it is found that the investment intensity of planning research has a time rule with urbanization and has different interactions in different stages of urbanization development. It was found that the intensity of planning research was strongly correlated with HDI, and the amount of research was crucial. [ABSTRACT FROM AUTHOR]

This study examined sleep research in athletes published between 1966 and 2019, through a bibliometric analysis of research output in the Scopus database. Following a robust assessment of titles, the bibliometric indicators of productivity for studies included in the final analysis were: Distribution of publications and citations (excluding self-citations), top ten active journals, countries, institutions and authors, single- and multi-country collaboration, and 25 top-cited papers. Out of the 1015 papers, 313 were included in the final analysis. The majority of the papers were research articles (n = 259; 82.8%) and published in English (n = 295; 94.3%). From 2011, there was a dramatic increase in papers published (n = 257; 82.1%) and citations (n = 3538; 91.0%). The number of collaborations increased after 2001, with papers published through international (n = 81; 25.9%) and national (n = 192; 61.3%) collaboration. Australia was the most prolific country in terms of number of publications (n = 97; 31.0%), and citations (n = 1529; 15.8%). In conclusion, after the beginning of the twenty-first century, the scientific production on sleep research in athletes has seen significant growth in publication and citation output. Future research should focus on interventions to improve sleep in athletes. [ABSTRACT FROM AUTHOR]

In this study, we undertake a comprehensive bibliometric analysis of the cybernetics research field. We compile a dataset of 4856 papers from the ISI Web of Science database spanning 1975–2022, employing keywords related to cybernetics. Our findings reveal an annual growth rate of 7.56% in cybernetics research over this period, indicating sustained scholarly interest. By examining the annual progression of scientific production, we have identified three distinct periods characterized by significant disruptions in yearly publication trends. These disruptions have been thoroughly investigated within the paper, utilizing a longitudinal analysis of thematic evolution. We also identify emerging research trends through keyword analysis. Furthermore, we investigate collaborative networks among authors, their institutional affiliations, and global representation to elucidate the dissemination of cybernetics research. Employing n-gram analysis, we uncover diverse applications of cybernetics in fields such as computer science, information science, social sciences, sustainable development, supply chain, knowledge management, system dynamics, and medicine. The study contributes to enhancing the understanding of the evolving cybernetics landscape. Moreover, the conducted analysis underscores the versatile applicability across various academic and practical domains associated with the cybernetics field. [ABSTRACT FROM AUTHOR]

Fake news is an explosive subject, being undoubtedly among the most controversial and difficult challenges facing society in the present-day environment of technology and information, which greatly affects the individuals who are vulnerable and easily influenced, shaping their decisions, actions, and even beliefs. In the course of discussing the gravity and dissemination of the fake news phenomenon, this article aims to clarify the distinctions between fake news, misinformation, and disinformation, along with conducting a thorough analysis of the most widely read academic papers that have tackled the topic of fake news research using various machine learning techniques. Utilizing specific keywords for dataset extraction from Clarivate Analytics' Web of Science Core Collection, the bibliometric analysis spans six years, offering valuable insights aimed at identifying key trends, methodologies, and notable strategies within this multidisciplinary field. The analysis encompasses the examination of prolific authors, prominent journals, collaborative efforts, prior publications, covered subjects, keywords, bigrams, trigrams, theme maps, co-occurrence networks, and various other relevant topics. One noteworthy aspect related to the extracted dataset is the remarkable growth rate observed in association with the analyzed subject, indicating an impressive increase of 179.31%. The growth rate value, coupled with the relatively short timeframe, further emphasizes the research community's keen interest in this subject. In light of these findings, the paper draws attention to key contributions and gaps in the existing literature, providing researchers and decision-makers innovative viewpoints and perspectives on the ongoing battle against the spread of fake news in the age of information. [ABSTRACT FROM AUTHOR]

The proliferation of misinformation presents a significant challenge in today's information landscape, impacting various aspects of society. While misinformation is often confused with terms like disinformation and fake news, it is crucial to distinguish that misinformation involves, in mostcases, inaccurate information without the intent to cause harm. In some instances, individuals unwittingly share misinformation, driven by a desire to assist others without thorough research. However, there are also situations where misinformation involves negligence, or even intentional manipulation, with the aim of shaping the opinions and decisions of the target audience. Another key factor contributing to misinformation is its alignment with individual beliefs and emotions. This alignment magnifies the impact and influence of misinformation, as people tend to seek information that reinforces their existing beliefs. As a starting point, some 56 papers containing 'misinformation detection' in the title, abstract, or keywords, marked as "articles", written in English, published between 2016 and 2022, were extracted from the Web of Science platform and further analyzed using Biblioshiny. This bibliometric study aims to offer a comprehensive perspective on the field of misinformation detection by examining its evolution and identifying emerging trends, influential authors, collaborative networks, highly cited articles, key terms, institutional affiliations, themes, and other relevant factors. Additionally, the study reviews the most cited papers and provides an overview of all selected papers in the dataset, shedding light on methods employed to counter misinformation and the primary research areas where misinformation detection has been explored, including sources such as online social networks, communities, and news platforms. Recent events related to health issues stemming from the COVID-19 pandemic have heightened interest within the research community regarding misinformation detection, a statistic which is also supported by the fact that half of the papers included in top 10 papers based on number of citations have addressed this subject. The insights derived from this analysis contribute valuable knowledge to address the issue, enhancing our understanding of the field's dynamics and aiding in the development of effective strategies to detect and mitigate the impact of misinformation. The results spotlight that IEEE Access occupies the first position in the current analysis based on the number of published papers, the King Saud University is listed as the top contributor for the misinformation detection, while in terms of countries, the top-5 list based on the highest contribution to this area is made by the USA, India, China, Spain, and the UK. Moreover, the study supports the promotion of verified and reliable sources of data, fostering a more informed and trustworthy information environment. [ABSTRACT FROM AUTHOR]

The importance of artificial intelligence in the banking industry is reflected in the speed at which financial institutions are adopting and implementing AI solutions to improve their services and adapt to new market demands. The aim of this research is to conduct a bibliometric analysis of the involvement of artificial intelligence in the banking sector to provide a comprehensive overview of the current state of research to guide future directions and support the sustainable development of this rapidly expanding field. Another important objective is to identify research gaps and underexplored areas in the field of artificial intelligence in banking. The methodology used is a bibliometric analysis using VOSviewer, analysing 1089 papers from the Web of Science database. The results of the study provide relevant information for banking professionals but also for policy makers. Thus, the study highlights key areas where banks are using artificial intelligence to gain competitive advantage, thereby guiding practitioners in strategic decision making. Moreover, by identifying emerging trends and patterns in AI adoption, the study helps banking practitioners with foresight, enabling them to anticipate and prepare for future developments in the field. In terms of governmental implications, the study can contribute to the development of more nuanced regulatory frameworks that effectively balance the promotion of AI innovation with the protection of ethical standards and consumer protection. [ABSTRACT FROM AUTHOR]

Due to budget and sensor technology constraints, a single sensor cannot simultaneously provide observational images with both a high spatial and temporal resolution. To solve the above problem, the spatiotemporal fusion (STF) method was proposed and proved to be an indispensable tool for monitoring land surface dynamics. There are relatively few systematic reviews of the STF method. Bibliometrics is a valuable method for analyzing the scientific literature, but it has not yet been applied to the comprehensive analysis of the STF method. Therefore, in this paper, we use bibliometrics and scientific mapping to analyze the 2967 citation data from the Web of Science from 1991 to 2023 in a metrological manner, covering the themes of STF, data fusion, multi-temporal analysis, and spatial analysis. The results of the literature analysis reveal that the number of articles displays a slow to rapid increase during the study period, but decreases significantly in 2023. Research institutions in China (1059 papers) and the United States (432 papers) are the top two contributors in the field. The keywords "Sentinel", "deep learning" (DL), and "LSTM" (Long Short-Term Memory) appeared most frequently in the past three years. In the future, remote sensing spatiotemporal fusion research can address more of the limitations of heterogeneous landscapes and climatic conditions to improve fused images' accuracy. [ABSTRACT FROM AUTHOR]

We survey the literature on the use of Benford's distribution digit analysis applied to COVID-19 case data reporting. We combine a bibliometric analysis of 32 articles with a survey of their content and findings. In spite of combined efforts from teams of researchers across multiple countries and universities, using large data samples from a multitude of sources, there is no emerging consensus on data misreporting. We believe we are nevertheless able to discern a faint pattern in the segregation of findings. The evidence suggests that studies using very large, aggregate samples and a methodology based on hypothesis testing are marginally more likely to identify significant deviations from Benford's distribution and to attribute this deviation to data tampering. Our results are far from conclusive and should be taken with a very healthy dose of skepticism. Academics and policymakers alike should remain mindful that the misreporting controversy is still far from being settled. [ABSTRACT FROM AUTHOR]

Bibliometric analysis is a rigorous method to analyze significant quantities of bibliometric data to assess their impact on a particular field. This study used bibliometric analysis to investigate the academic research on diabetes detection and classification from 2000 to 2023. The PRISMA 2020 framework was followed to identify, filter, and select relevant papers. This study used the Web of Science database to determine relevant publications concerning diabetes detection and classification using the keywords "diabetes detection", "diabetes classification", and "diabetes detection and classification". A total of 863 publications were selected for analysis. The research applied two bibliometric techniques: performance analysis and science mapping. Various bibliometric parameters, including publication analysis, trend analysis, citation analysis, and networking analysis, were used to assess the performance of these articles. The analysis findings showed that India, China, and the United States are the top three countries with the highest number of publications and citations on diabetes detection and classification. The most frequently used keywords are machine learning, diabetic retinopathy, and deep learning. Additionally, the study identified "classification", "diagnosis", and "validation" as the prevailing topics for diabetes identification. This research contributes valuable insights into the academic landscape of diabetes detection and classification. [ABSTRACT FROM AUTHOR]

Rising population levels exert significant pressure on available freshwater resources. Scientists and researchers from various countries are diligently seeking a long-lasting solution using solar-powered desalination. This research paper investigates the current advancements in solar desalination research by utilizing the method of "scientometrics". Scientometrics employs traditional methodologies, including bibliometrics, which entails quantifying the number of research papers published, and citation analysis, which involves examining the frequency with which other researchers cite these papers. By integrating these two approaches, scientometrics provides invaluable information about the most influential countries, institutions, and individual researchers in the field. Utilizing the software program VOSviewer, a comprehensive analysis was conducted on 1855 research papers published between 2010 and 2024. These papers were selected based on a predetermined set of ten key search terms. The results of the analysis indicate that China is the leading country in this field, as it boasts the highest number of published papers and the most citations received overall. Notably, Egyptian research institutions have been identified as the most influential in this area. Moreover, a single author has notably amassed 3419 citations for their 54 published works on solar desalination. This analysis unveiled past and contemporary advancements in the field and identified current trends through keyword analysis. It also offers recommendations based on bibliometric findings, including suggestions for addressing the challenges faced by solar-derived systems and addressing research area saturation. [ABSTRACT FROM AUTHOR]

Simple Summary: The present work presents a snapshot of the state of the art of Equine-Assisted Intervention (EAI) research, including published articles and the most cited research as well as the most used keywords, and prolific authors and co-authors and their countries. To our knowledge, no other bibliometric studies have been performed, so it can be a tool to support future research. Equine Assisted Interventions (EAIs) integrate the active participation of horses in therapeutic or educational interventions. A bibliometric analysis was carried out on this topic, using traditional bibliometric laws and recommendations. For this purpose, a search on the Web of Science (WoS) Core Collection database was carried out, obtaining 333 documents. Annual publications followed an exponentially increasing trend (R2 = 86%), pointing out that this topic is a growing interest among researchers, publishers, and journals. The USA was the most productive country worldwide and Jeong-yi Kwon and Ji Lee were the prolific co-authors. The WoS category with the highest number of papers was Rehabilitation (84 papers). The Journal of Alternative and Complementary Medicine, and Pediatric Physical Therapy were the journals with the highest number of publications. The most cited paper was "State of the Evidence Traffic Lights 2019: Systematic Review of Interventions for Preventing and Treating Children with Cerebral Palsy". The most used author keywords were rehabilitation, balance, and those related to specific populations such as Cerebral Palsy and Autism Spectrum Disorder. These results suggest that EAIs is a topic of increasing interest for researchers, editors, and professionals. [ABSTRACT FROM AUTHOR]

Simple Summary: Different reproductive biotechnologies have been applied to sheep, such as cloning, which has been successfully applied in this species. In this context, the aim of the present study was to carry out a bibliometric analysis of the scientific literature on cloning applied to sheep reproduction, since the first report was published, to identify the most cited articles, main authors and collaboration among them, published journals, institutions with more published papers, most prolific countries and the network collaboration among them, and research topics. This study collected bibliographic data from 124 papers relating to cloning of sheep. The articles that were cited more often addressed topics related to the generation of transgenic animals, recovery of wild species, and xenotransplants. So far, no bibliometric studies have been conducted about cloning of sheep. Somatic cell nuclear transfer (SCNT) is a reproductive biotechnology with great potential in the reproduction of different species of zootechnical interest, including sheep. This study aimed to carry out a bibliometric analysis of scientific papers published on the application of SCNT in sheep reproduction during the period 1997–2023. The search involved the Science Citation Index Expanded and Social Sciences Citation Index databases of the main collection of the Web of Sciences with different descriptors. A total of 124 scientific papers were analyzed for different bibliometric indicators using the VOSviewer software. Since 2001, the number of SCNT-related papers that have been published concerning sheep reproduction has increased and it has fluctuated in ensuing years. The main authors, research groups, institutions, countries, papers, and journals with the highest number of papers related to the application of SCNT in sheep reproduction were identified, as well as the topics that address the research papers according to the terms: somatic cell, embryo, oocyte, gene expression, SCNT, and sheep. [ABSTRACT FROM AUTHOR]

This paper presents a bibliometric analysis of battery state estimation in electric vehicles. In this paper, a quick study is performed on the top global research contributors, funding agencies, and affiliate universities or institutes performing research on this topic while also finding the top keyword searches and top authors based on the most citations in the field of electric vehicles. Trend analysis is done by using the SCOPUS and Web of Science (WOS) databases (DB) from the period of 2000 to 2021. Battery state estimation plays a major role in the battery present state based on past experience. Battery available charge and health knowledge is a must for range estimation and helps us acknowledge if a battery is in useful condition or needs maintenance or replacement. A total of 136 documents in SCOPUS and 1311 documents in Web of Science were analyzed. Through this bibliometric analysis, we learn the top authors, country, publication journal, citation, funding agency, leading documents, research gap, and future trends in this research direction. The author Xiong Rui has the most publications, and he is working at the Beijing Institute of Technology, China. The most common institution is the Beijing Institute of Technology, and China is the most highly contributing country in this research. Most of the publications are conference types in SCOPUS DB and article types in WOS DB. The National Natural Science Foundation of China provides the most funding. The journal Energies has the most publications related to this field. The most cited works are by the authors M.A. Hannan and L.G. Lu in SCOPUS and WOS DB, respectively. A statistical analysis of the top ten countries' productivity results is also discussed. [ABSTRACT FROM AUTHOR]

Bibliometric analysis is an effective method used to identify research trends based on historical publications that involves combining different frameworks, tools and methods, leading to the creation of different metrics. This study employed bibliometric analysis to investigate the global health risk assessment of heavy metals in food from 2000 to 2022 using Web of Science and VOSviewer. We explore publication trends, affiliations, countries, journals, citations, keywords and author collaborations. Of the 573 publications on this topic, there has been a notable increase in recent years. The Ministry of Agriculture and Rural Affairs (China) and Shahid Beheshti University of Medical Sciences (Iran) are the most prolific affiliations. Environmental Science and Pollution Research is the top journal. Notably, "heavy metals", "risk assessment", "cadmium", "lead", and "trace elements" are frequently used keywords. A study by Miraglia et al. in 2009 received the most citations. Amin Mousavi Khaneghah (Poland) is the most prolific author, with 24 papers. Articles mainly focus on contamination levels in fish, seafood, cereals, dairy, meat, and fruit/vegetables. Some studies highlight potential risks, necessitating stricter food product controls for consumer safety. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is revolutionizing the textile industry by improving the prediction of fabric properties and handfeel, which are essential for assessing textile quality and performance. However, the practical application and translation of AI-predicted results into real-world textile production remain unclear, posing challenges for widespread adoption. This paper systematically reviews AI-driven techniques for predicting these characteristics by focusing on model mechanisms, dataset diversity, and prediction accuracy. Among 899 papers initially identified, 39 were selected for in-depth analysis through both bibliometric and content analysis. The review categorizes and evaluates various AI approaches, including machine learning, deep learning, and hybrid models, across different types of fabric. Despite significant advances, challenges remain, such as ensuring model generalization and managing complex fabric behavior. Future research should focus on developing more robust models, integrating sustainability, and refining feature extraction techniques. This review highlights the critical gaps in the literature and provides practical insights to enhance AI-driven prediction of fabric properties, thus guiding future textile innovations. [ABSTRACT FROM AUTHOR]

A company's "value" is increasingly influenced by three criteria: the way it acts to protect the environment, its attitude towards society and the principles of corporate governance it has adopted. That is the Environmental, Social and Governance (ESG) acronym, and it has substantial impact on company value. To further understand the ESG landscape in business research, this article aims to analyze the existing literature and present the current state of knowledge, main trends, and future perspectives. Through the Scopus database, the authors examine a sample of 1034 articles spanning from 2006 to 2022. VOSviewer and Biblioshiny packages are used for performance analysis and visualization of the publication trends, the conceptual structure of the field and the research collaborations. The results suggest that the publication and citation trends of ESG register an upward trend over time. In terms of research institutions, most of the influential ones emanate from the US, while a significant percentage of articles were published in top-tier financial journals. Science mapping via co-authorship analysis bifurcates the sample into six clusters and reveals the major themes and their evolution. Keyword analysis unfolds emerging trends that could be further explored. Given the breadth of the sustainability field and the ever-changing business environment, this paper is of great practical importance in motivating companies to engage in ESG activities. To the authors' knowledge, no other study has attempted a comprehensive and detailed BA covering multiple aspects and dimensions of ESG in the corporate research field. The theoretical framework of this paper fills this gap and offers an in-depth synthesis of all published papers, providing invaluable insights to scholars, the business community and regulatory authorities, and creating alternative research paths for aspiring researchers. [ABSTRACT FROM AUTHOR]

Since their creation, geoparks have been among the fastest growing natural environments. Their attractiveness is one of the most important factors for the success of this natural destination. Despite their importance, a bibliometric analysis on geopark attractiveness is missing from the studied databases. The aim of this paper is to synthesise a heterogeneous body of knowledge of geoparks in terms of attractiveness, highlighting the evolution and breadth of the research field. To achieve this, the following objectives were set: (a) to adopt a method based on functions provided by the bibliometrix package to automatically combine databases, namely WoS, Scopus, PubMed and Dimensions, detailing the method used and (b) to analyse the bibliometric indicators in order to identify the trends in the literature and the possible directions for future research. The applied methodology was based on bibliometric analysis using R for non-coders. From the 707 documents retrieved, the validation process resulted in 349 eligible documents published between 2002 and 2024, on which the analysis was carried out. The current study elaborated a method and examined the key information on the topic trends, which were given by production performance, productivity trends, spatial analysis and abstract approach analysis. Additionally, strategic mapping of the conceptual context was performed. Thus, the result provides a description of the automatic method with practical applications. As discerned from the three-dimensional analysis (spatial, temporal and size), the emerging research directions within scientific creativity encompassed (1) forms of tourism practiced in geoparks, especially focused on ecotourism and volcanic tourism; (2) geomorphological features, mineral springs and mud volcanoes; (3) aesthetic aspects, scenic sites and mining heritage; and (4) methodology, data analysis and modelling methods across different regions and countries. [ABSTRACT FROM AUTHOR]

Managing the fragmented nature of information generated on construction sites and firms is the need of the hour. Building Information Modeling (BIM) and Enterprise Resource Planning (ERP) are the most prevalent information systems (ISs) used in the construction industry, with varied capabilities but also with significant overlap. It is essential to analyze the current state of Common Data Environments (CDEs) that support both BIM and ERP as separate systems, as well as those that facilitate their integration. This analysis will ultimately help establish a practical framework for implementing this integration, enabling smoother information flow and enhanced utilization in construction projects. This paper presents a bibliometric analysis and provides a global perspective on research developments in the field of construction ERP and its integrations with BIM. It consolidates publication data from various databases (e.g., Scopus and Web of Science) as per geographical spread, authors, and number of publications as per the keyword search. It observes key research themes in each phase of the analysis. This paper concludes that although the existing literature has established the benefits of BIM and ERP integration, research is still in its nascent stage and identifies research gaps that can be taken up for further research. [ABSTRACT FROM AUTHOR]

River and lake health assessment (RLHA) is an important approach to alleviating the conflict between protecting river and lake ecosystems and fostering socioeconomic development, aiming for comprehensive protection, governance, and management. Vegetation, a key component of the riparian zone, supports and maintains river and lake health (RLH) by providing a range of ecological functions. While research on riparian zone vegetation is ongoing, these studies have not yet been synthesized from the perspective of integrating RLHA with the ecological functions of riparian zone vegetation. In this paper, based on the bibliometric method, the relevant literature studies on the topics of RLHA and unmanned aerial vehicle (UAV) remote sensing of vegetation were screened and counted, and the keywords were highlighted, respectively. Based on the connotation of RLH, this paper categorizes the indicators of RLHA into five aspects: water space: the critical area from the river and lake water body to the land in the riparian zone; water resources: the amount of water in the river and lake; water environment: the quality of water in the river and lake; water ecology:aquatic organisms in the river and lake; and water services:the function of ecosystem services in the river and lake. Based on these five aspects, this paper analyzes the key role of riparian zone vegetation in RLHA. In this paper, the key roles of riparian zone vegetation in RLHA are summarized as follows: stabilizing riverbanks, purifying water quality, regulating water temperature, providing food, replenishing groundwater, providing biological habitats, and beautifying human habitats. This paper analyzes the application of riparian zone vegetation ecological functions in RLH, summarizing the correlation between RLHA indicators and these ecological functions. Moreover, this paper analyzes the advantages of UAV remote sensing technology in the quantitative monitoring of riparian zone vegetation. This analysis is based on the high spatial and temporal resolution characteristics of UAV remote sensing technology and focuses on monitoring the ecological functions of riparian zone vegetation. On this basis, this paper summarizes the content and indicators of UAV quantitative remote sensing monitoring of riparian zone vegetation for RLHA. It covers several aspects: delineation of riparian zone extent, identification of vegetation types and distribution, the influence of vegetation on changes in the river floodplain, vegetation cover, plant diversity, and the impact of vegetation distribution on biological habitat. This paper summarizes the monitoring objects involved in monitoring riparian zones, riparian zone vegetation, river floodplains, and biological habitats, and summarizes the monitoring indicators for each category. Finally, this paper analyzes the challenges of UAV quantitative remote sensing for riparian zone vegetation at the current stage, including the limitations of UAV platforms and sensors, and the complexity of UAV remote sensing data information. This paper envisages the future application prospects of UAV quantitative remote sensing for riparian zone vegetation, including the development of hardware and software such as UAV platforms, sensors, and data technologies, as well as the development of integrated air-to-ground monitoring systems and the construction of UAV quantitative remote sensing platforms tailored to actual management applications. [ABSTRACT FROM AUTHOR]

Background and Objectives: Accelerated orthodontics represents a significant shift in dental practice aimed at reducing treatment times while maintaining optimal patient outcomes. This bibliometric analysis evaluated the research landscape of accelerated orthodontics from 2012 to 2023, focusing on publication trends, citation patterns, influential journals, leading institutions, and key contributors. Materials and Methods: A comprehensive search in Scopus identified 600 relevant articles, with the top 50 most-cited papers encompassing systematic reviews, randomized controlled trials, and experimental studies. Key techniques, such as corticotomy and piezocision, have been frequently highlighted for their effectiveness in expediting tooth movement. Results: The analysis revealed fluctuating annual scientific outputs, with notable peaks driven by technological advancements and increased patient demand for quicker orthodontic solutions. However, the production of high-impact papers was hindered by delays in citation accumulation and disruptions caused by the COVID-19 pandemic. Keyword analysis identified critical themes, such as orthodontic tooth movement, malocclusion, and demographic factors, while a global collaboration map underscored extensive international research partnerships. Leading journals included the American Journal of Orthodontics and Dentofacial Orthopedics, and prominent institutions such as the University of California at Los Angeles played significant roles in advancing the field. Conclusions: This study provides a comprehensive overview of the current state of accelerated orthodontics, emphasizing the need for continued research, particularly RCTs, to further refine and validate accelerated orthodontic techniques and improve clinical outcomes. [ABSTRACT FROM AUTHOR]

In this paper, we examine the relationship between open banking and tax evasion. As the open banking literature is still evolving, we try to systematically analyze the literature on conventional banking and tax evasion and then extend the discussion in the context of open banking. The popularity of open baking recently raises a question about its relationship with tax evasion. Digital banking and digital taxation contributed positively to mitigating tax evasion in the context of conventional banking. However, in open banking, the customers can decide to what extent they will share any transaction-related data with their bank, while they can also choose to complete direct transactions with third parties. This creates a new challenge in relation to the mitigation of tax evasion, which is the focus of this paper. Due to lack of granular empirical data, we conduct a systematic literature review and a bibliometric analysis to track the development of the relevant academic debates and identify the arguments that have been presented in relation to this topic. This approach is recognized as well suited for emerging topics in finance research, particularly when data are scarce, as evidenced by studies on COVID-19 and biodiversity. We find that the gaps of the current regulatory framework, at both the national and supranational level, have created challenges and uncertainties at multiple levels. Nonetheless, the findings of the study suggest future research directions and offer valuable guidelines for regulators in utilizing open banking. [ABSTRACT FROM AUTHOR]

Social entrepreneurship plays an important role in the maintenance of economic prosperity and brings benefits to society. The role of social entrepreneurship is growing in the light of challenges of the global economy, increasing uncertainty of the environment, the growth of social problems, and the emergence of crises in the 2020s. These derive an increase in economic and psychological challenges. Social entrepreneurship is known as the driver for solving global problems of society. The entrepreneurial ecosystem serves as a source of entrepreneurial opportunity, as a breeding ground for entrepreneurship. Therefore, exploring the topic of social entrepreneurship in the context of the entrepreneurial ecosystem becomes relevant. Social entrepreneurship, with respect to the entrepreneurial ecosystem, has been extensively explored. However, despite a growing body of publications, to the best of our knowledge, no bibliometric analysis is available on the topic. This analysis is important to understand what trends in the development of social entrepreneurship and the ecosystem exist, what further research directions can be recommended, and how the relationship between social entrepreneurship and the entrepreneurial ecosystem has been studied. This study aims to close the gap, consolidate research, and identify the state of the art in the field. In total, 357 publications from the Scopus database were selected for the period of 2009–2022. The study used social network analysis (bibliographic coupling network, co-citation network, citation network, and co-authorship network) and semantic analysis (semantic network) through VOSviewer version 1.6.19 and Gephi version 0.10.1 software. The results showed a growth of publications during this period, allowing us to observe influential journals, the most productive and cited authors, leading countries and universities, impactful papers, networks of collaborations, and co-citations of scholars. The paper with the highest degree of centrality is "Ecosystems in Support of Social Entrepreneurs: A Literature Review" while Sustainability is the most influential journal in the field. The analysis identified six thematic clusters within the research topic. The study contributes to the literature by presenting the research agenda, structure, characteristics of social entrepreneurship, and entrepreneurial ecosystem research. [ABSTRACT FROM AUTHOR]

This paper addresses the challenges in forecasting electrical energy in the current era of renewable energy integration. It reviews advanced adaptive forecasting methodologies while also analyzing the evolution of research in this field through bibliometric analysis. The review highlights the key contributions and limitations of current models with an emphasis on the challenges of traditional methods. The analysis reveals that Long Short-Term Memory (LSTM) networks, optimization techniques, and deep learning have the potential to model the dynamic nature of energy consumption, but they also have higher computational demands and data requirements. This review aims to offer a balanced view of current advancements and challenges in forecasting methods, guiding researchers, policymakers, and industry experts. It advocates for collaborative innovation in adaptive methodologies to enhance forecasting accuracy and support the development of resilient, sustainable energy systems. [ABSTRACT FROM AUTHOR]