Keyword Co-occurrence Network Research Articles

Bibliometric Analysis of Artificial Intelligence in the Scope of E-Commerce: Trends and Progress over the Last Decade

Artificial intelligence (AI) techniques are commonly used in e-commerce, but there is little bibliometric analysis in this field. Using a bibliometric approach, it conducted a comprehensive study over the past decade to assess the research landscape, progress, and emerging trends in the field of artificial intelligence in e-commerce. Data was collected from related literature in the Scopus database from 2014 to the first half of 2023. VOSviewer and R studio were used to perform the bibliometric analysis of AI in e-commerce. The author status, nations, affiliations, annual publications, keywords, and journals were all evaluated in this way. The oldest relevant article was published in 1994, and article reviews were the most common form of document among the 669 manuscripts. Furthermore, the most popular research areas in this topic are business, management, and accounting. Additionally, the most productive journal is Proceedings of the International Conference on Electronic Business (ICEB). Moreover, the UK is the country that has published the most articles, and in terms of co-authorship, it has the strongest overall link. Finally, the keyword co-occurrence network indicates that the most important keywords are machine learning, e-commerce, recommender systems, fraud detection, decision-making systems, data mining, and online retailing.

Analyzing the Research Progress of Campsites in China and Internationally: A CiteSpace-Based Approach

This study leverages CiteSpace to create a keyword co-occurrence network for camping site research, aiming to outline the current state and development trends in this field, both globally and in China. The analysis highlights that international research focuses on camper behaviors, experiences, and the ecological and managerial aspects of camping sites. In contrast, Chinese research centers on industry status, market positioning, and development strategies, with a greater emphasis on specific site planning and management. The study reveals a notable gap between Chinese and international research in terms of breadth and depth. Chinese studies are predominantly qualitative and lack a focus on ecological and humanistic considerations, leading to limited generalizability of findings. This comparison underscores the need for a more integrated and quantitative approach in Chinese camping site research, aligning with global standards and incorporating a stronger emphasis on ecological preservation and humanistic values.

Scientometric analysis of quantum-inspired metaheuristic algorithms

Quantum algorithms, based on the principles of quantum mechanics, offer significant parallel processing capabilities with a wide range of applications. Nature-inspired stochastic optimization algorithms have long been a research hotspot. The fusion of quantum mechanics with optimization methods can potentially address NP-hard problems more efficiently and exponentially faster. The potential advantages provided by the ground-breaking paradigm have expedited the scientific output of quantum-inspired optimization algorithms locale. Consequently, a pertinent investigation is required to explain how ground-breaking scientific advancements have evolved. The scientometric approach utilizes quantitative and qualitative techniques to analyze research publications to evaluate the structure of scientific knowledge. Henceforth, the current research presents a scientometric and systematic analysis of quantum-inspired metaheuristic algorithms (QiMs) literature from the Scopus database since its inception. The scientometric implications of the article offer a detailed exploration of the publication patterns, keyword co-occurrence network analysis, author co-citation analysis and country collaboration analysis corresponding to each opted category of QiMs. The analysis reveals that QiMs solely account to 26.66% of publication share in quantum computing and have experienced an impressive 42.59% growth rate in the past decade. Notably, power management, adiabatic quantum computation, and vehicle routing are prominent emerging application areas. An extensive systematic literature analysis identifies key insights and research gaps in the QiMs knowledge domain. Overall, the findings of the current article provide scientific cues to researchers and the academic fraternity for identifying the intellectual landscape and latest research trends of QiMs, thereby fostering innovation and informed decision-making.

Infants on the move: bibliometric analyses of observational vs. digital means of screening infant development.

Neurodevelopmental disorders are on the rise, yet their average diagnosis is after 4.5 years old. This delay is partly due to reliance on social-communication criteria, which require longer maturation than scaffolding elements of neuromotor control. Much earlier criteria could include reflexes, monitoring of the quality of spontaneous movements from central pattern generators and maturation of intentional movements and their overall sensation. General Movement Assessment (GMA) studies these features using observational means, but the last two decades have seen a surge in digital tools that enable non-invasive, continuous tracking of infants' spontaneous movements. Despite their importance, these tools are not yet broadly used. In this work, using CiteSpace, VOSViewer and SciMAT software, we investigate the evolution of the literature on GMA and the methods in use today, to estimate how digital techniques are being adopted. To that end, we created maps of key word co-occurrence networks, co-author networks, document co-citation analysis and strategic diagrams of 295 publications based on a search in the Web of Science, Dimensions and SCOPUS databases for: 'general movement assessment' OR 'general movements assessment'. The nodes on the maps were categorized by size, cluster groups and year of publication. We found that the state-of-the-art methodology to diagnose neurodevelopmental disorders still relies heavily on observation. Several groups in classical GMA research have branched out to incorporate new techniques, but few groups have adopted digital means. We report on additional analyses of methods and biosensors usage and propose that combining traditional clinical observation criteria with digital means may allow earlier diagnoses and interventional therapies for infants.

Public procurement research: a bibliometric analysis

PurposeThe literature on public procurement (PP) has increased significantly in recent years, and, to date, several reviews have been conducted to study this relevant subject. Nevertheless, a bibliometric analysis of the PP knowledge domain is still missing. To fill this knowledge gap, a bibliometric review is carried out to investigate the current state of PP research.Design/methodology/approachA total of 640 journal articles are selected from the Scopus database for the final analysis. The performance indicators of the literature are identified and explained through bibliometric analysis. Furthermore, the conceptual and intellectual structures are studied through a keyword co-occurrence network and bibliographic coupling.FindingsThe results of the review indicate that PP research has increased significantly in recent years. The top ten most productive journals, countries, authors and academic institutions are identified. The findings from the keyword co-occurrence network reveal six main research themes including innovation, corruption and green public procurement (GPP). By applying bibliographic coupling, the focus of PP research revolves around seven thematic areas: GPP, corruption, the role of small and medium-sized enterprises (SMEs) in PP, electronic PP, innovation, labour standards and service acquisition. The research potential of each thematic area is evaluated using a model based on maturity and recent attention (RA).Originality/valueTo the best of the authors' knowledge, this is the first study to successfully organise, synthesise and quantitatively analyse the development of the PP domain amongst a large number of publications on a large time scale.

A corpus-based bibliometric study of highly cited papers in sport sciences

Highly cited papers showcase high-quality research and encompass significant themes in the field. This study examined a total of 435 highly cited papers based on Essential Citation Indicators in the Web of Science (WoS) category of sport sciences with a bibliometric method. In particular, the bibliometric indicators of the highly cited papers including publication venues, authors, countries, institutions, and the top cited publications were presented and analyzed in detail. An Abstract corpus was constructed to help identify the most frequently explored topics. VOSviewer was employed to visualize the co-occurrence networks of keywords. The study revealed the trending information of important contributors at the levels of journals, authors, countries, and institutes. The top cited publications can be grouped into three categories: guidelines, recommendations based on systematic reviews, and evaluations. The most frequently explored topics based on the Abstract corpus and the most frequently used keywords from VOSviewer mapping overlap to a great extent. Specifically, topics such as meta-analysis, systematic review, sport-related concussion, sedentary behavior, football, rehabilitation, and osteoarthritis are among the most frequently mentioned. The results provide the most updated publication characteristics and hot topics of highly cited papers in sport sciences and offer insights for academic researchers in future research.

Analysing trends and patterns in retrenchment research: a bibliometric approach

In today’s highly competitive business market, the optimization of operational efficiency and expense reduction is crucial for firms to maintain profitability and ensure long-term sustainability. A popular corporate strategy for achieving such goals is retrenchment, which involves shrinking or reorganizing organizational activities. The significance of conducting a bibliometric study on retrenchment lies in its ability to offer valuable insights to scholars, policymakers, and stakeholders interested in retrenchment and implementation and how it impacts employees and organisations. The review further identifies trends and patterns in retrenchment, highlighting significant works, and presenting a comprehensive understanding of it as a corporate strategy. To evaluate the research on labour retrenchment, a document search was conducted using article titles and keywords, analysing published documents and their citations. The data on publications were obtained from the Scopus database for this study. The VOS viewer tool was utilized to visualize the data derived from Scopus, while Harzing’s Publish or Perish programme (Windows GUI Edition) was employed to analyse the citations and performance indicators of the publications. The findings reveal a total of 79 documents published by 177 writers between 1982 and 2023. There is evidence that the sum of publications on retrenchment has been steadily snowballing over time necessitating attention. The study observed a global interest in retrenchment research, with contributions from various countries and across multiple subject areas. The study also examined the top 26 most cited publications on retrenchment, showing variations in citation numbers and rates over time. Keyword co-occurrence network analysis identified significant groupings in retrenchment research. These clusters offer a comprehensive view of retrenchment research which adequately covers a range of themes, including the healthcare industry in the United States, the intersection of retrenchment and healthcare, the psychological effects, economic factors, and ethical implications.

토픽모델링과 ERGM에 기반한 디지털 신기술에 대한 트위터 데이터의 키워드 분석

Artificial intelligence, big data, internet of things, autonomous driving, and blockchain are emerging digital technologies that are contributing significantly to society as essential drivers of the Fourth Industrial Revolution. We analyzed people's demands and identified the main fields that need to be nurtured by examining the Korean and English keywords related to digital technologies mentioned on Twitter. We selected keywords related to digital technologies and performed LDA topic modeling, dividing the data into three periods: the second half of 2020 and the first and second half of 2021. We also generated co-occurrence networks to understand the interconnection structure of the keywords. As the COVID-19 pandemic continued, we observed the emergence of topics related to metaverse services, which gained popularity in virtual environments. Artificial intelligence, cloud, and blockchain have high connections to various keywords in all three periods for Korean tweets. On the other hand, blockchain played a central role in English tweets. We applied ERGMs by utilizing press and research indices as node attributes in the Korean keyword co-occurrence networks. Throughout all the periods, the research index positively affects keyword connections. On the other hand, the press index has a negative effect on keyword connections, suggesting that the media might not accurately grasp public trends.

Analyzing the impact of sustainable economic development from the policy text network: Based on the practice of China's bay area policy.

In order to break through the surface analysis of the content structure of policy texts, an in-depth discussion of the linkage between regional policy makers and objectives is helpful to analyze the formation mechanism of policy effects. Through social network analysis and multi-index analysis, this study takes the QianwanNew Area of Ningbo and the Guangdong-Hong Kong-Macao Greater Bay Area as representatives to explore the policy framework for the sustainable development of manufacturing industry in the two bay areas respectively. Through the construction of government department cooperation network, policy keyword co-occurrence network, department keyword correlation network, and the analysis of network density, network centrality, structural holes, and cohesive subgroups, it is found that the impact results show great differences, which is related to the network structure of manufacturing policy text.

A KEYWORD CO-OCCURRENCE ANALYSIS OF RESEARCH ON SPIRITUALITY FROM AN ISLAMIC PERSPECTIVE BETWEEN 2018 TO 2022: EMERGING RESEARCH TRENDS

The article provides a detailed overview of the extant literature on spirituality from Islamic perspectives as well as it reveals the trends and suggests future research directions for scholars who wish to contribute to this rapidly growing field. A bibliometric analysis was conducted using data obtained from the Scopus database by searching articles, book chapters, and manuscripts containing the term “spirituality” AND “Islamic perspectives” OR “views” OR “concept” on their titles, abstracts, and/or keywords. Publish or Perish, and VOSviewer software were then used to obtain publication trends, citation index per year, highly cited articles, and keyword co-occurrence network. There is a fluctuating trend of publication on spirituality from an Islamic perspective such that a decrease occurred in 2021 compared to the years prior. Although 2018 has the highest total citations (n=351) and average citations per article (5.40), 2021 has the highest number of cited publications (n=116) which suggest a notable presence of influential works in the year 2021. Some of the themes with the highest keyword co-occurrence are well-being (27 items), clinical studies (26 items), Islamic thoughts and civilization (13 items), and medical ethics (5 items). There are abundant articles published within the year 2018 to 2022 regarding spirituality from an Islamic perspective and the bibliometric analysis found emerging trends specifically on themes of well-being, clinical studies, and Islamic thoughts and civilization which future researchers can focus on.

Generation of graphs from scientific journal metadata with the OAI-PMH system

Access to scientific and scholarly information has become more accessible than ever before, in large part due to the proliferation of scholarly journals that use metadata systems to expose their content. Notable examples of these systems include the Open Journal Systems (OJS) and the Objects of Learning Metadata Protocol (OAI-PMH), which have significantly simplified the dissemination of research online. However, as these platforms have become essential for research publication and dissemination, new needs arise for publishers and scholars. A technological innovation-type study was conducted by generating codes for primary data generation with the ultimate goal of generating graphs for co-authorship networks and co-occurrence of terms. This paper focuses on a solution to this growing demand for enriched information. We will explore how generating graphs from scholarly journal metadata using the OAI-PMH system can address these specific needs. The generation of graphs from scholarly journal metadata using the OAI-PMH system and Python codes offers a powerful and versatile approach to the analysis of scholarly output. This study demonstrates the applicability of this methodology in the generation of keyword co-occurrence networks and co-authorship networks, providing a deeper and more contextual view of scientific publications. The relevance of this application extends to editors of academic journals as well as to scholars and researchers. For publishers, this tool facilitates the effective presentation of their journals, the evaluation of the quality and content of publications, the selection of categories for indexing, and the identification of emerging trends. On the other hand, for academics, this methodology fosters collaboration, enables more advanced bibliometric analyses, facilitates the presentation of results, and supports informed decision-making in their research areas.

Exploring and Visualizing Research Progress and Emerging Trends of Event Prediction: A Survey

Over the last decade, event prediction has drawn attention from both academic and industry communities, resulting in a substantial volume of scientific papers published in a wide range of journals by scholars from different countries and disciplines. However, thus far, a comprehensive and systematic survey of recent literature has been lacking to quantitatively capture the research progress as well as emerging trends in the event prediction field. Aiming at addressing this gap, we employed CiteSpace software to analyze and visualize data retrieved from the Web of Science (WoS) database, including authors, documents, research institutions, and keywords, based on which the author co-citation network, document co-citation network, collaborative institution network, and keyword co-occurrence network were constructed. Through analyzing the aforementioned networks, we identified areas of active research, influential literature, collaborations at the national level, interdisciplinary patterns, and emerging trends by identifying the central nodes and the nodes with strong citation bursts. It reveals that sensor data has been widely used for predicting weather events and meteorological events (e.g., monitoring sea surface temperature and weather sensor data for predicting El Nino). The real-time and multivariable monitoring features of sensor data enable it to be a reliable source for predicting multiple types of events. Our work offers not only a comprehensive survey of the existing studies but also insights into the development trends within the event prediction field. These findings will assist researchers in conducting further research in this area and draw a large readership among academia and industrial communities who are engaged in event prediction research.

The track, hotspot and frontier of anammox technology in wastewater treatment 2001–2022

Anaerobic ammonia oxidation (anammox) technology is gaining traction as a promising solution for wastewater denitrification due to its ability to reduce investment, and minimize operational costs and sludge production. As a result, it has become a hot research topic of wastewater treatment, with a growing body of literature exploring its potential applications. However, despite the increasing interest in this field, there is a lack of comprehensive analysis that provides a clear overview of the development context and quantitative research on the overall trends of anammox technology in wastewater treatment. To manage this gap, this article conducted a systematic bibliometric analysis of global application research of anammox technology in wastewater treatment using VOSviewer, CiteSpace, and Bibliometric for the core collection database of Web of Science. The study included drawing a collaborative map of countries, institutions, and researchers to display the distribution of research forces and scientific research cooperation in this field. Moreover, the article employed software co-occurrence analysis to obtain the hot scientific fields in anammox wastewater treatment. Finally, valuable insights into the future direction of research in this field were provided through the use of a keyword co-occurrence network atlas and literature co-citation network atlas, which were employed to analyze research hotspots, research frontiers, and development trends.

Driving Circular Economy through Digital Technologies: Current Research Status and Future Directions

The transition from a linear economy (LE) to a circular economy (CE) is not just about mitigating the negative impacts of LE, but also about considering changes in infrastructure, while leveraging the power of technology to reduce resource production and consumption and waste generation, and improve long-term resilience. The existing research suggests that digital technologies (DTs) have great potential to drive the CE. However, despite the exponential growth and increasing interest in studies on DTs and the CE from year 2016 onwards, few systematic studies on the application of DTs to enable the CE have been found. In addition, the current status and development direction of the DT-driven CE is unclear, and the potential of DTs to support CE implementation is under-researched. Therefore, the aim of this paper is to explore the potential of DTs to drive the CE. This paper set out to analyze the current status and development of the DT-driven CE and examine future development trends in the field. Using a systematic literature review approach, this paper is the first attempt to use a mixed method, i.e., to combine macro-quantitative bibliometric methods with a micro-qualitative content analysis method to explore the DT-driven CE. The results, which include the research background, co-occurrence clusters, research hotspots, and development trends of keyword co-occurrence network visualization and keyword burst detection, are presented from a macro perspective using two bibliometric analysis softwares. In addition, the use of 13 specific DTs in the CE is analyzed according to seven disciplinary areas (Environmental Sciences and Ecology, Engineering, Science and Technology and Other Topics, Business Economics, Computer Science, Operations Research and Management Science, and Construction and Building Technology) of greatest interest from a micro-qualitative point of view. Further, future trends and challenges facing DT-driven CE development are explored and feasible directions for solutions are proposed.

Looking Back on its Fiftieth Year - Bibliometric and Scientometric Analysis of the Articles Published in the Journal of Psychology and Theology from 1996 to 2022

The Journal of Psychology and Theology was started in 1973 when the growth of psychology encroached into the arena of Theology, thereby aiming to integrate the two. OBJECTIVE AND APPROACH: As the journal completes its 50th year, this study reviews its journey through a bibliometric and scientometric analysis of the articles available in the Scopus database (26 years) using four analyses – publication, citation, network, and thematic. RESULT AND DISCUSSION: The results show that 70% of the top contributing institutions were Christian institutions, and the USA contributed to 90% of the articles. The top three keywords were ‘Virtues’, ‘Positive Psychology’, and ‘Integration’, showing how positive psychology bridged the two fields. Factorial analysis segregated the topics into two main groups: Values and Beliefs. Keywords co-occurrence network generated 5 clusters – Subject Integration, Theoretical Integration, Positive Psychology, Spirituality, and Clergy and its Issues. RECOMMENDATION: To increase author networking and articles featuring theological perspectives from other continents and other faiths.

A bibliometric and scientific mapping of the research landscape and trending topics in building integrated photovoltaic systems

The present article aims to identify emerging trends in the building integrated photovoltaic (BIPV) field through an analysis of the most prominent articles, authors, keywords, sources, and countries through bibliometric analysis of the same. To fulfil the study's aims, 1552 articles published in Scopus databases between 1985 and 2022 are reviewed and analysed using the Bibliometrix - R software, VOSviewer, and SciMAT. Since 2016, the results indicated that the number of publications per year in this domain has consistently increased. The China, UK, and USA were the most prominent contributors to this research area in terms of overall publications and citations. In addition, the results highlight the most significant sections of the article from the perspective of the highest citations, publications, keywords, and authors. Through co-citation analysis and keyword co-occurrence network, the major knowledge base and the most prominent hot themes of BIPV study field were identified. The minimum number of co-occurrences of keywords is set to the value of five which results in 166 threshold keywords out of these 146 keywords are selected and divided into 9 clusters. Cluster-1 (Red) contains a total of 32 keywords. BIPV has the highest connection of 63 links and 67 documents followed by phase change material (52 links and 45 documents). The results pointed to a potential gap in the literature regarding the use of artificial neural networks in BIPV systems.

Event Knowledge Graph: A Review Based on Scientometric Analysis

In the last decade, the event knowledge graph field has received significant attention from both academic and industry communities, leading to the proliferated publication of numerous scientific papers in diverse journals, countries, and disciplines. However, a comprehensive and systematic survey of the recent literature in this area to obtain how the development of event knowledge graph evolves over time is lacking. To address this gap, we performed scientometric analyses utilizing the CiteSpace software of version 6.2.R4 package to extract and analyze data from the Web of Science database, including information about authors, journals, countries, and keywords. We then constructed four networks, including the author co-citation network, journal co-citation network, collaborative country network, and keyword co-occurrence network. Analyzing these networks allowed us to identify core authors, research hotspots, landmark journals, and national collaborations, as well as emerging trends by assessing the central nodes and nodes with strong citation bursts. Our contribution mainly lies in providing a scientometric way to quantitatively capture the research patterns in the last decade in the event knowledge graph field. Our work provides not only a structured view of the state-of-the-art literature but also insights into future trends in the event knowledge graph field, aiding researchers in conducting further research in this area.

Enchanting performance measurement and management with data envelopment analysis: Insights from bibliometric data visualization and analysis

While the breadth of applicative uses of data envelopment analysis (DEA) has increased over time, this non-parametric frontier methodology has proven effective for measuring how efficient decision-making units (DMUs) are. One of its uses is performance measurement in various organizations — from universities and banks to investment funds and entrepreneurial small and medium-sized enterprises. Following a search inquiry in the Scopus and Web of Science databases, we found no bibliometric analysis and keyword co-occurrence network visualization of just the use of DEA for performance management. With this study, we attempt to investigate the DEA literature for performance measurement and management, considering articles in scientific peer-reviewed journals, which are indexed in the Web of Science database. The analysis and visualization of the bibliometric data are based on 89 articles from the start of the century onward. We present the annual trends of published articles, journals, authors, and countries leading the scientific discussion and citation analysis. A detailed keyword visualization analysis was performed and is discussed in this article alongside the paths for future hotspots of the use of DEA for performance management. The findings have implications for both the academic community and practitioners, business leaders, managers, and policy-makers.

Research Trends and Hot Spots of Allopregnanolone Research in the Last 20 Years: A Bibliometric Analysis.

Allopregnanolone is a kind of neuroactive steroid or neurosteroid in the central nervous system that acts as an endogenenous GABAA receptor positive modulator. However, at present, no comprehensive bibliometric analysis regarding allopregnanolone research is available. In our study, we intend to analyze the research trends and hot spots related to allopregnanolone in the past 20 years. We searched for allopregnanolone related articles and reviews between 2004 and 2023 from the Web of Science Core Collection database. Then, the bibliometric analysis was conducted using VOSviewer, CiteSpace, Microsoft Excel 2019, as well as the online bibliometric analysis platform (http://bibliometric.com/). A total of 1841 eligible publications were identified. The number of annual publications and citations was generally on the rise. Among countries, the United States ranked first in overall publications, citations, international cooperation, and the number of research institutions. The University of North Carolina was the most active institution, conducting numerous preclinical and clinical work that focusing on allopregnanolone treatment for diverse psychiatric or neurologic disorders. As for authors, Dr. Frye CA, Morrow AL, and Pinna G were identified as the top three prolific scholars due to their great publications and citations. Based on the publication clusters and citation bursts analysis, the keyword co-occurrence network, the strongest citation bursts, and co-cited references analysis, the hot spots in recent years included "depression", "postpartum depression", "GABAA receptor", and so on. Allopregnanolone is still a popular area of research, and the United States leads the way in this area. Dr. Frye CA, Morrow AL, Pinna G, and their teams contributed greatly to the mechanism study and translation study of allopregnanolone. The use of allopregnanolone for the treatment of psychiatric or neurologic disorders, especially postpartum depression, is the current hot spot. However, the underlying mechanisms of anti-depression are still not clear, deserving more in-depth research.

대학 학생성공 해외 연구동향 분석: 상세 서지정보 분석

The purpose of this study was to examine international research trends with respect to student success in the field of higher education. In order to address the study’s purpose, we collected scholarly articles that addressed issues and topics concerning student success published between 1974 and 2023. This study employed bibliometric analysis targeted towards bibliometric information of a total of 615 articles housed in SSCI- and Scopus-indexed journals. The information was extracted from the Web of Science, a web database powered by Clarivate Analytics. For data analysis, we utilized the bibliometrix package in RStudio. The study’s findings show that the quantity of articles on student success has increased since the late 2000s, especially surging since the mid-2010s. The majority of these investigations were conducted in Western countries, predominantly the United States, and international collaboration was scarce. Through the frequency analysis of co-citation data, author, and key terms, it was revealed that the foundational underpinnings of student success have been rooted in the concepts of student retention and student engagement. According to the results of keyword co-occurrence network analysis, we categorized sub-themes into five clusters: (a) teaching and learning assessments within online environments, (b) institutional support and empirical approaches for student retention, (c) psychological and emotional aspects responding to student crisis, (d) student engagement and experience-based student-oriented perspectives, and (e) associations with adult education and career development in community colleges. Finally, the study’s findings from thematic analysis demonstrate that research on student success has emerged based on inter- and intra-collaborations within and across various domains of studies. Based on the findings, academic and practical implications are suggested for research and practice in South Korea’s higher education context.