Theme Mapping and Bibliometrics Analysis of One Decade of Big Data Research in the Scopus Database

Intersections of Big Data and IoT in Academic Publications: A Topic Modeling Approach

As vast amounts of data are generated from various sources such as social media, sensors and online transactions, the analysis of Big Data offers organizations the ability to derive insights and make informed decisions. Simultaneously, IoT connects physical devices, enabling real-time data collection and exchange that transforms interactions within smart homes, cities and industries. The intersection of these fields is essential, leading to innovations such as predictive maintenance, real-time traffic management and personalized solutions. Utilizing a dataset of 8159 publications sourced from the Web of Science database, our research employs Natural Language Processing (NLP) techniques and selective human validation to analyze abstracts, titles, keywords and other useful information, uncovering key themes and trends in both Big Data and IoT research. Six topics are extracted using Latent Dirichlet Allocation. In Topic 1, words like "system" and "energy" are among the most frequent, signaling that Topic 1 revolves around data systems and IoT technologies, likely in the context of smart systems and energy-related applications. Topic 2 focuses on the application of technologies, as indicated by terms such as "technologies", "industry" and "research". It deals with how IoT and related technologies are transforming various industries. Topic 3 emphasizes terms like learning and research, indicating a focus on machine learning and IoT applications. It is oriented toward research involving new methods and models in the IoT domain related to learning algorithms. Topic 4 highlights terms such as smart, suggesting a focus on smart technologies and systems. Topic 5 touches upon the role of digital chains and supply systems, suggesting an industrial focus on digital transformation. Topic 6 focuses on technical aspects such as modeling, system performance and prediction algorithms. It delves into the efficiency of IoT networks with terms like "accuracy", "power" and "performance" standing out.

Bioprospecting of Aspergillus sp. as a promising repository for anti-cancer agents: a comprehensive bibliometric investigation

Cancer remains a significant global health challenge, claiming nearly 10 million lives in 2020 according to the World Health Organization. In the quest for novel treatments, fungi, especially Aspergillus species, have emerged as a valuable source of bioactive compounds with promising anticancer properties. This study conducts a comprehensive bibliometric analysis to map the research landscape of Aspergillus in oncology, examining publications from 1982 to the present. We observed a marked increase in research activity starting in 2000, with a notable peak from 2005 onwards. The analysis identifies key contributors, including Mohamed GG, who has authored 15 papers with 322 citations, and El-Sayed Asa, with 14 papers and 264 citations. Leading countries in this research field include India, Egypt, and China, with King Saud University and Cairo University as the leading institutions. Prominent research themes identified are "endophyte," "green synthesis," "antimicrobial," "anti-cancer," and "biological activities," indicating a shift towards environmentally sustainable drug development. Our findings highlight the considerable potential of Aspergillus for developing new anticancer therapies and underscore the necessity for further research to harness these natural compounds for clinical use.

Does medical waste research during COVID-19 meet the challenge induced by the pandemic to waste management?

The COVID-19 pandemic has resulted in an unprecedented amount of medical waste, presenting significant challenges for the safe disposal of hazardous waste. A systematic review of existing research on COVID-19 and medical waste can help address these challenges by providing insights and recommendations for effective management of the massive medical waste generated during the pandemic. This study utilized bibliometric and text mining methods to survey the scientific outcomes related to COVID-19 and medical waste, drawing on data from the Scopus database. The results show that the spatial distribution of medical waste research is unbalanced. Surprisingly, developing countries rather than developed countries lead research in this area. Especially, China, a major contributor to the field, has the highest number of publications and citations, and is also a centre of international cooperation. The main study authors and research institutions are also mainly from China. And the research on medical waste is a multidisciplinary field. Text mining analysis shows that COVID-19 and medical waste research is mainly organized around four themes: (i) medical waste from personal protective equipment; (ii) research on medical waste in Wuhan, China; (iii) threats of medical waste to the environment and (iv) disposal and management of medical waste. This would serve to better understand the current state of medical waste research and to provide some implications for future research.

Exploring the scientific research on coal fly ash and agriculture: knowledge mapping and future research directions

This paper aims at synthesizing the scientific research on coal fly ash and agriculture using bibliometric analysis. The research on fly ash and agriculture has grown at 6.7% annually during 1973-2022, where much attention has been received after 2007. The number of publications on coal fly ash and agriculture reached above 100 in the year 2010, which further increased to 299 by 2020. The research productivity has been assessed as the most influential countries, journals, and documents in terms of a number of publications and citations on fly ash and agriculture. India is the most productive country in terms of knowledge on coal fly ash and agriculture with 38% of the global publications, while Environmental Science and Pollution Research is the leading journal with 19 publications. The article on assessing the impact of fly ash incorporation in soil systems by Pandey and Singh (2010), having 349 citations with 26.85 citations per year is one of the leading publications globally. Further, science mapping has been conducted to comprehend the current research focus and discover the emerging themes for future research. The finding of the thematic map based on the level of development and importance indicate that FA can be effectively explored as soil-additive for improved physical, chemical and biological properties and enhanced plant nutrients. The findings provide several aspects of fly ash and suggest future research directions to study the potential of using coal fly ash in agriculture to gain an agronomic advantage.

Bibliometric Examination of Global Scientific Research about Carbapenem-Resistant Acinetobacter Baumannii (CRAB)

This review paper presents a comprehensive bibliometric analysis of the global scientific research pertaining to carbapenem-resistant Acinetobacter baumannii (CRAB) from the years 1996 to 2023. The review employs a systematic approach to evaluate the trends, patterns, and collaborative networks within the CRAB research landscape, shedding light on its substantial global health implications. An analysis of the Scopus database reveals that the earliest publication within the CRAB research domain dates back to 1996. By conducting a meticulous examination of publication output, citation trends, author affiliations, and keyword distributions, this paper provides valuable insights into the evolution of research themes and the emergence of new areas of interest concerning CRAB. The findings of this bibliometric analysis prominently feature the most influential author within this field, namely, Higgins PG, who has contributed a remarkable 39 documents to CRAB research. It is noteworthy that China leads in terms of the quantity of published research articles in this domain, whereas the United States occupies the foremost position about citations within the CRAB research sphere. Furthermore, a more profound exploration of the data yields a heightened understanding of the current status of CRAB research, emphasizing potential avenues for future investigations and underscoring the imperative need for collaborative initiatives to address the challenges posed by this antibiotic-resistant pathogen.

Evolution and trends of hikikomori: a bibliometrics analysis

Hikikomori is the Japanese term for the phenomenon of young adults isolating themselves from society and becoming reclusive. This study aims to examine the evolution and distribution of hikikomori, as well as identify the major players and institutions involved in hikikomori research. The searches, which were conducted in Scopus database identified 286 academic research works pertaining to hikikomori research. The findings indicate that hikikomori has attracted the attention of academic researchers in both the East and the West, with a consistent increase in research output since the Internet revolution over the past decade. The study highlights the potential for additional research on hikikomori and provides a benchmark for new researchers entering the field.

Evolution of Tick Vaccinology Highlights Changes in Paradigms in This Research Area

Ticks and tick-borne diseases affect human and animal health worldwide. Although some tick-protective antigens have been identified and characterized, further research is needed for the development and application of effective anti-tick vaccines, which currently are unavailable for human protection. To study the trends and gaps in anti-tick vaccine approaches, herein we used scientometric analysis to evaluate several aspects of tick vaccinology. Co-authorship and citations networks pointed out two main research fronts, one focused on the laboratory protocols driving the recognition of candidate antigens and the other devoted to field experiments of protection against ticks. The analysis demonstrated the prominence of research in European countries on the topic. The scientometric approach allowed the recognition of isolated teams working casually on the topic, the lack of cooperation between middle- and low-income countries, and the need for sustained and integrated research. Most important, we identified a considerable lack of new candidates for vaccine development, as well as the participation of African and Asian countries. These results provide significant insights obtained from bibliographical analysis, suggest the strength and weaknesses in this field of research, and highlight new directions to advance in the development of effective vaccines for the control of tick infestations and tick-borne pathogens.

A scientometric study on application of electrochemical sensors for detection of pesticide using graphene-based electrode modifiers

Pesticide testing is an important topic in environmental protection and food safety. The development of green, accurate and reliable pesticide residue detection methods is an important technical support for implementing of agricultural quality supervision. Electrochemical sensors are a very promising analytical method for pesticide detection due to their high sensitivity, speed, low cost and portability. Performance enhancement of electrochemical sensors is often accompanied by research advances in materials science. Among them, carbon material is a very important electrode material for the fabrication of electrochemical sensors. The discovery of graphene makes it the most promising candidate among carbon materials for sensor performance enhancement. The topic of this review is the use of graphene-modified electrochemical sensors for pesticide detection in the last decade. Traditional literature summaries and bibliometric analyses were used for an in-depth analysis of this topic. In addition to the introduction of different sensor types and performance comparisons, this review also parses the authors' country, keywords and publication frequency. The related research experienced rapid growth several years ago and has now reached a relatively stable stage. We also discuss the perspectives on this topic.

A Bibliometric Analysis of the Scientific Research on Artisanal and Small-Scale Mining

Mineral resource exploitation is one of the activities that contribute to economic growth and the development of society. Artisanal and small-scale mining (ASM) is one of these activities. Unfortunately, there is no clear consensus to define ASM. However, its importance is relevant in that it represents, in some cases, the only employment alternative for millions of people, although it also significantly impacts the environment. This work aims to investigate the scientific information related to ASM through a bibliometric analysis and, in addition, to define the new lines that are tending to this field. The study comprises three phases of work: (i) data collection, (ii) data processing and software selection, and (iii) data interpretation. The results reflect that the study on ASM developed intensively from 2010 to the present. In general terms, the research addressed focuses on four interrelated lines: (i) social conditioning factors of ASM, (ii) environmental impacts generated by ASM, (iii) mercury contamination and its implication on health and the environment, and (iv) ASM as a livelihood. The work also defines that geotourism in artisanal mining areas is a significant trend of the last decade, explicitly focusing on the conservation and use of the geological and mining heritage and, in addition, the promotion of sustainable development of ASM.

Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites

In order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, we propose a design and research method of a short text mining tool based on the K-means clustering algorithm and Kano mode. An improved short text clustering algorithm is used to extract the design elements of laptops. Based on the traditional questionnaire, we extract the user’s attention factors, score the emotional tendency, and analyze the user’s needs based on the Kano model. Then, we select 10 laptops, process them by the improved algorithm, cluster the evaluation words and quantify the emotional orientation matching. Based on the obtained data, we design a visual interaction logic and usability test. These prove that the proposed method is feasible and effective.

[Thematic analysis of Primary Care journals indexed in Journal Citation Reports: 2015-2019]

OBJECTIVE

Analyze the thematic lines of the articles and reviews published between 2015 and 2019 in the journals indexed in the "Primary Health Care" category of the Journal Citation Reports.

METHODS

Observational bibliometric study. The bibliographic records of the Web of Science were identified and the frequencies of appearance of the thematic descriptors and their co-occurrence in the documents included in the study were analyzed. In addition to the global analysis, the reviews, the most cited documents, those published in 2015, and those published in 2019 were analyzed separately. Descriptors were classified by thematic clusters using the Current Canadian Index scale and clinical publications were analyzed using the second edition of the International Classification of Primary Care.

RESULTS

A total of 16,444 descriptors were identified in the 7,453 documents analyzed. The most frequent descriptors focus on: diagnosis, prevalence, management, risks, care practice and the figure of the health professional. In the most cited documents, terms with specific themes were used: depression, intervention, satisfaction, quality, therapy, research-based practice. In 2019, there were a greater number of publications focused on epidemiology, clinic, research and provision of services. From a clinical point of view, studies on psychological and mental health problems, nervous system, social problems, palliative care and cancer increased in 2019.

CONCLUSIONS

The analysis carried out identifies the relevant thematic lines in primary care journals, highlighting the diagnosis and prevalence of diseases, the management of pathologies and their associated risks, as well as clinical practice and the figure of the health professional.

Effects of Diesel, Heavy Metals and Plastics Pollution on Penguins in Antarctica: A Review

Simple Summary

Antarctica is contaminated by anthropogenic pollution. Due to the persistent low temperatures, the toxic impacts of pollution to the environment can be extensive. The severity of the effects varies according to the animal species, chemical type and level of exposure. Penguins are at major risk as they are the most prominent group of animals in Antarctica. This review highlights the background of penguins in Antarctica, the anthropogenic pollution and cases, as well as the toxic effects of diesel, heavy metals and microplastics toward penguins. A bibliometric analysis is also included.

Abstract

Antarctica is a relatively pristine continent that attracts scientists and tourists alike. However, the risk of environmental pollution in Antarctica is increasing with the increase in the number of visitors. Recently, there has been a surge in interest regarding diesel, heavy metals and microplastics pollution. Contamination from these pollutants poses risks to the environment and the health of organisms inhabiting the continent. Penguins are one of the most prominent and widely distributed animals in Antarctica and are at major risk due to pollution. Even on a small scale, the impacts of pollution toward penguin populations are extensive. This review discusses the background of penguins in Antarctica, the anthropogenic pollution and cases, as well as the impacts of diesel, heavy metals and microplastics toxicities on penguins. The trends of the literature for the emerging risks of these pollutants are also reviewed through a bibliometric approach and network mapping analysis. A sum of 27 articles are analyzed on the effects of varying pollutants on penguins in Antarctica from 2000 to 2020 using the VOSviewer bibliometric software, Microsoft Excel and Tableau Public. Research articles collected from the Scopus database are evaluated for the most applicable research themes according to the bibliometric indicators (articles, geography distribution, annual production, integrated subject areas, key source journals and keyword or term interactions). Although bibliometric studies on the present research theme are not frequent, our results are sub-optimal due to the small number of search query matches from the Scopus database. As a result, our findings offer only a fragmentary comprehension of the topics in question. Nevertheless, this review provides valuable inputs regarding prospective research avenues for researchers to pursue in the future.

Thematic Analysis of Military Medical Ethics Publications From 2000 to 2020-A Bibliometric Approach

Introduction

There has been external criticism of the compliance of military health personnel with internationally agreed principles in military medical ethics (MME). In response, a number of authors have called for clarity on the principles and topics within the domain of MME. This complements an increased acknowledgment of the need for education in MME for military health personnel. Our paper utilizes bibliometric techniques to identify key themes in MME to inform the development of a curriculum for this subject.

Materials and Methods

We designed a search strategy to find publications over the period January 1, 2000-December 31, 2020 in the domain of MME from the three databases, PubMed, Web of Science, and Scopus, using the search string (ethic* OR bioethics* OR moral*) AND military AND (medic* OR health*). We obtained a total of 1,115 publications after duplication removal. After exclusion based on topic, year, and study design, we analyzed a total of 633 publications using Scopus’s embedded analysis tool and the software VOSViewer. We generated a co-occurrence word map from the abstracts of each of the publications. We deduced themes of MME based on the clusters shown in the word map, and we categorized each publication into one of these themes to analyze the change of themes over time.

Results

We observed a 10-fold increase in annual publications on MME between 2000 and 2020. The majority of papers were written by U.S. (72%) and UK (13%) authors, although a total of 15 countries were represented. After using VOSViewer to identify co-occurring keywords in titles and abstracts from these publications, nine themes were identified: biomedical research, care to detained populations, disaster/triage, mental health, patient-focused foundations, technology, dual loyalty, education/training, and frameworks. The relative proportion of each of these themes changed over the study period, with mental health being dominant by the end.

Conclusions

This study has identified key themes that might inform the development of a curriculum for teaching MME. It is noticeable that the majority of themes cover MME from the perspective of professional practice on military operations; noting, the research and technology themes also pertain to the generation of knowledge for military operations. There were a limited number of publications covering practice in the non-deployed or garrison settings, and these were codified under the themes of “framework” and “dual loyalty”. The results are skewed toward English-speaking countries and exclude non-academic publications. Further work will search for other open-source information and non-English publications. To our knowledge, this exploratory bibliometric analysis on MME in the academic literature is the first of its kind. This article has demonstrated the use of bibliometric techniques to evaluate the evolution of knowledge in MME, including the identification of key themes. These will be used to support further work to develop a curriculum for the teaching of MME to military medical audiences.

A scalable eigenspace-based fuzzy c-means for topic detection

Purpose

The aim of this research is to develop an eigenspace-based fuzzy c-means method for scalable topic detection.

Design/methodology/approach

The eigenspace-based fuzzy c-means (EFCM) combines representation learning and clustering. The textual data are transformed into a lower-dimensional eigenspace using truncated singular value decomposition. Fuzzy c-means is performed on the eigenspace to identify the centroids of each cluster. The topics are provided by transforming back the centroids into the nonnegative subspace of the original space. In this paper, we extend the EFCM method for scalability by using the two approaches, i.e. single-pass and online. We call the developed topic detection methods as oEFCM and spEFCM.

Findings

Our simulation shows that both oEFCM and spEFCM methods provide faster running times than EFCM for data sets that do not fit in memory. However, there is a decrease in the average coherence score. For both data sets that fit and do not fit into memory, the oEFCM method provides a tradeoff between running time and coherence score, which is better than spEFCM.

Originality/value

This research produces a scalable topic detection method. Besides this scalability capability, the developed method also provides a faster running time for the data set that fits in memory.

Big Data in Business: A Bibliometric Analysis of Relevant Literature

This special issue was open for submissions in the field of big data in business. Accordingly, this special issue includes five contributions to the fields of business process innovation in the big data era, unstructured big data analytical methods in firms, online analytical processing approach for business intelligence in big data, geospatial insights for retail recommendation using similarity measures, and big data and operational changes through interactive data visualization. A bibliometric approach is used to visualize and highlight the exciting literature on big data followed by highlighting the contribution of this special issue.