Text Mining Analysis Research Articles

Uncertainty in underground mining operations: a bibliometric and systematic literature review analysis

Purpose This study aims to provide a comprehensive review of the existing literature on uncertainty in underground mining operations, using a bibliometric and systematic analysis covering the period from 1975 to 2024. Design/methodology/approach To achieve this, the following questions were addressed using a mixed-method approach involving bibliometrics, text mining and content analysis: How has the field of uncertainty research in underground mining operations evolved? What are the most prominent research topics and trends in uncertainty in underground mining operations? and What are the possible directions for future research on uncertainty in underground mining operations? Findings As a result, bibliometric networks of 327 journal articles from the Scopus database were created and examined, the main research topics were underground mining management; rock mechanics; operational optimization; and stochastic systems. Finally, the inclusive investigation of uncertainty in underground mining operations and its prominent patterns can serve as a basis for real-time direction for new research and as a tool to improve underground mining activities by implementing advanced technology for innovative practices and optimizing operational efficiency. This is fundamental to identify unknown variables that impair the planning, operation, safety and economic viability of underground mines. Originality/value This research is 100% original because there is no review research on the uncertainty present in underground mining operations.

Enteric Methane Emission in Livestock Sector: Bibliometric Research from 1986 to 2024 with Text Mining and Topic Analysis Approach by Machine Learning Algorithms

Methane (CH4) from livestock, particularly enteric CH4 emission (EME), is one contributor to greenhouse gas emissions and climate change. This review analyzed 1294 scientific abstracts on EME in ruminants from 1986 to May 2024, using Scopus® data. Descriptive statistics, text mining, and topic analysis were performed. Publications on EME have risen significantly since 2005, with the Journal of Dairy Science being the most frequent publisher. Most studies (82.1%) were original research, with Northern Hemisphere countries leading in publication numbers. The most frequent terms were “milk”, “cow”, and “diet”, while key research topics included greenhouse gas emissions from livestock, diet composition, and prediction models. Despite progress, some areas like CH4 emission from animals need further investigation.

Big Data Analysis on Consumer Perception of Pressure Injuries: Text Mining and Semantic Network Analysis

Background: With the ultimate goal of developing chatbot content to address consumer inquiries about pressure injuries (PIs), this study analyzed consumer perceptions of PI using big data.Methods: This study collected text data, with PI as the central word, from three search engines (Naver, Daum, Google) from January 2019 through December 2022, using Textom version 4.5. The words were refined through text mining, keyword analysis, and TF-IDF (term frequency-inverse document frequency) analysis. N-gram analysis and centrality visualization were conducted using Ucinet 6.0. The keywords and frequencies were clustered based on the frequency of words used in CONCOR (convergence of iteration correlation) analysis.Results: Consumers for PI showed a high perception of common sites for PI, concept of PI, healthcare facility for PI, PI products, PI care, PI-related life, and PI-related disease.Conclusion: Development of chatbot content customized to consumers’ needs, based on seven clusters associated with consumers’ perception of PI obtained through extensive data analysis with PI as the central word, is expected to make a significant contribution to improving consumers’ understanding of PI and enhancing the quality of PI management.

Exploring the patterns of China's carbon neutrality policies

To achieve the ambitious carbon neutrality goal by 2060, the Chinese government has implemented a series of carbon neutrality policies. These policy documents are pivotal in facilitating the examination of policy substance, the scrutiny of policy evolution, and the dissection of the policy instruments involved. This study develops an analytical framework for assessing carbon neutrality through policy documents, applying text mining and network analysis to probe the intricacies of policy topics, interagency collaboration, and diffusion dynamics. This research aims to delineate and expound upon the strategic paradigms employed by the Chinese government in its quest for carbon neutrality. The findings reveal a constellation of eleven policy topics, with "green" and "low carbon" being key aspects of each. The policy collaboration network has a density of 0.593, and the National Development and Reform Commission (NDRC)'s high average weighted degree of 14.6 highlights its crucial role in leading and coordinating these policies. In terms of diffusion dynamics, the green energy transition topic has a diffusion speed of 0.967 and a strength of 49, indicating its importance to the Chinese government. On a practical level, the findings offer policy-makers concrete, actionable recommendations to refine policy design and enhance implementation effectiveness. Theoretically, this study advances the scientific understanding of policy dynamics by proposing a novel analytical framework that integrates multiple dimensions of policy analysis, contributing to the methodological development of policy research.

Assessment of Perceptions of Human Papillomavirus (HPV) Vaccine Among Japanese Healthcare Professional University Students Using Text Mining Analysis

Assessment of Perceptions of Human Papillomavirus (HPV) Vaccine Among Japanese Healthcare Professional University Students Using Text Mining Analysis

Utilising Text Mining to Determine Japanese Dental Hygiene Students' Perceptions of Dental Hygienists and Dentists.

This longitudinal text-mining study examines dental hygiene students' perceptions of dental hygienists and dentists at three different points in time during their training course. The null hypothesis of the study was that there would be no change in the dental hygiene students' perceptions of the dental hygienists and dentists over the course of 3 years. First-year dental hygiene students participated in this study beginning with the academic year 2020. The questionnaires were conducted in 2020, 2021, and 2022. Participants were asked to write their perceptions of dental hygienists and dentists on the questionnaire sheets, and a quantitative text-mining analysis was performed. Initially, 59 female students were assessed for enrollment in this study, and the overall participation rate was 88.1%. The first-year students' perceptions of dental hygienists were "assist" and "beside" the dentist based on the co-occurrence group, while in the second-year, "cleaning" and "tooth" emerged in this group, and a new group of "cordinal-listen-story" materialised. In the third year, these groups merged into one group centered on "kind." In the perceptions of dentists, the word "fear" was the most frequent before clinical training, while the frequency of the world "kind" increased after clinical training. The word "treat" was ranked third in the second year of curriculum and then first in the final year. The null hypothesis was rejected. It can be concluded that if interactions between dental hygiene and dental students are systematically incorporated from early undergraduate education, clinical practice will be more meaningful and lead to stronger intraprofessional collaboration in future clinical practice.

A thorough overview of the literature on waste recycling in the circular economy: current practices and future perspectives.

To develop a circular economy (CE) and protect the environment, waste recycling (WR) is crucial. This study examines WR research conducted over the past two decades to identify the most significant advancements and promising areas for future research. The following challenges were handled through text mining, content, and bibliometrics analysis: How has CE influenced the evolution of WR research? What are the CE's most important WR research trends and themes? What directions could future research on WR take regarding the CE transition? Using 1118 articles from the Scopus database journal, bibliometric networks were made and analyzed. Hence, five critical CE-related problems needing further research were recognized: waste recycling is the first cluster, followed by technology, the CE transformation, plastic waste, and waste management (WM). Examining WM and inclusive waste reduction practices and their distinct highlight patterns may impact future research fields and serve as a transitional tool to CE (which aims to minimize waste generation). Forthcoming research targets contain waste reduction and incorporation of WR into the CE framework.

Perceptions and responses to diseases among patients with inflammatory bowel disease: text-mining analysis of posts on a Japanese patient community website

Introduction: Patients with inflammatory bowel disease (IBD) are increasingly using online platforms to communicate with other patients and healthcare professionals seeking disease-related information and support. Free-text posts on these platforms could provide insights into patients’ everyday lives, which could help to improve patient care. In this proof-of-concept study, we applied text-mining to extract patient needs from free-text posts on a community forum in Japan, and holistically visualized the patients’ perceptions and their connections, and explored the patient characteristic-dependent trends in the use of words. Methods: Free-text posts written between May 11, 2020 and May 31, 2022 on the community forum were retrieved and subjected to text-mining analysis. Trends in the use of words were extracted from the posts for correspondence and co-occurrence network analyses using KH Coder open-source text-mining software. Results: Seventy-four posts were analyzed. Using text mining methods, we successfully extracted and visualized a variety of patient concerns and their connections. The correspondence and co-occurrence analyses revealed patient segment-dependent trends in the use of words. For example, patients with a disease duration of ≤5 yrs were more likely to use words related to emotions or their desire to change or quit their job, such as ‘anxiety’ and ‘resignation.’ Patients with a disease duration of >10 yrs were more likely to use words showing that they are finding ways to live with or accept their disease, and are getting used to the lifestyle but some patients continued to experience worsening disease. Conclusions: We found that free texts posted on an IBD community forum can be a useful source of information to capture the wide variety of thoughts of patients. Text mining procedures can help to visualize the relative importance of the topics identified from free text posts. Our findings of this proof-of-concept study will be useful for generating new hypotheses to better understand and address the needs of patients with IBD.

The mining of China's policies against COVID-19 based on a policy target and tool co-evolution framework

Mining all COVID-19 policies issued by China can provide valuable lessons for both China and other countries in future pandemic control efforts. In this paper, we introduce a novel framework for mining the co-evolution of policy targets and policy tools. We employ bibliometric methods, text mining, and network analysis to explore the entire evolution of China's COVID-19 policies. Examining 1154 central government policies, (a) we extract policy targets from each policy, uncovering their evolution across different stages of the pandemic; (b) propose to identify the policy tool used in each policy unit by integrating an automatic identification model and active learning. We also reveal the categorical structure of these tools; (c) characterize the co-evolution pattern between policy targets and policy tools, shedding light on their dynamic relationship. Our findings indicate that policy targets have shifted across various stages, revealing unique characteristics in China's COVID-19 prevention and control efforts. Notably, there is a self-paradox between prevention measures and economic development. We identify the inadequateness in the distribution and utilization of policy tools. Ensuring the alignment of policy targets with appropriate tools is crucial. This synchronization and co-evolution between policy targets and tools are essential for enhancing the functional approach to policy implementation. This paper is the first systematic mining and review about the COVID-19 policies issued by the Chinese government, and our policy target and tool co-evolution mining framework provides a new quantitative framework for policy mining, especially an improved large language model and active learning theory are integrated to identify the policy tools automatically.

Trends and Gaps in the Scientific Literature about the Effects of Nutritional Supplements on Canine Leishmaniosis.

In canine leishmaniosis (CanL), complex interactions between the parasites and the immunological background of the host influence the clinical presentation and evolution of infection and disease. Therefore, the potential use of nutraceuticals as immunomodulatory agents becomes of considerable interest. Some biological principles, mainly derived from plants and referred to as plant-derived nutraceuticals, are considered as supplementation for Leishmania spp. infection. This study provides a systematic review regarding the use of nutraceuticals as a treatment using a text mining (TM) and topic analysis (TA) approach to identify dominant topics of nutritional supplements in leishmaniosis-based research, summarize the temporal trend in topics, interpret the evolution within the last century and highlight any possible research gaps. Scopus® database was screened to select 18 records. Findings revealed an increasing trend in research records since 1994. TM identified terms with the highest weighted frequency and TA highlighted the main research areas, namely "Nutraceutical supports and their anti-inflammatory/antioxidant properties", "AHCC and nucleotides in CanL", "Vit. D3 and Leishmaniosis", "Functional food effects and Leishmaniosis" and "Extract effects and Leishmaniosis". Despite the existing academic interest, there are only a few studies on this issue so far, which reveals a gap in the literature that should be filled.

OriTDB: a database of the origin-of-transfer regions of bacterial mobile genetic elements.

Conjugation and mobilization are two important pathways of horizontal transfer of bacterial mobile genetic elements (MGEs). The origin-of-transfer (oriT) region is crucial for this process, serving as a recognition site for relaxase and containing the DNA nicking site (nic site), which initiates the conjugation or mobilization. Here, we present a database of the origin-of-transfer regions of bacterial MGEs, oriTDB (https://bioinfo-mml.sjtu.edu.cn/oriTDB2/). Incorporating data from text mining and genome analysis, oriTDB comprises 122 experimentally validated and 22927 predicted oriTs within bacterial plasmids, Integrative and Conjugative Elements, and Integrative and Mobilizable Elements. Additionally, oriTDB includes details about associated relaxases, auxiliary proteins, type IV coupling proteins, and a gene cluster encoding the type IV secretion system. The database also provides predicted secondary structures of oriT sequences, dissects oriT regions into pairs of inverted repeats, nic sites, and their flanking conserved sequences, and offers an interactive visual representation. Furthermore, oriTDB includes an enhanced oriT prediction pipeline, oriTfinder2, which integrates a functional annotation module for cargo genes in bacterial MGEs. This resource is intended to support research on bacterial conjugative or mobilizable elements and promote an understanding of their cargo gene functions.

How Customer Value and Customer Self Construal Influence Repurchase Intentions Moderated by Customer’s Country Origin: Study of Gen Z in Indonesia-Malaysia

This research aims to analyse the influence of Customer (perceived) Value and Self-construal in Gen Z on their decision to repurchase fashion products online in e-commerce such as e-Matahari, Zalora, and Pomelo, with country of origin as the moderating variable. This research uses the SEM-PLS method with SmartPLS software to analyse 236 data generated from online questionnaires to consumers in Indonesia and Malaysia. This research variable was determined after conducting text mining analysis using the orange application, which produces keywords and sentiment analysis to become a reference in deciding variables. The results of the study show that Customer (perceived) Value and Self-construal are directly able to influence Repurchase Intention significantly. At the same time, the country of origin cannot moderate this influence.

Text Mining and Topic Analysis for Ostriches' Welfare Based on Systematic Literature Review from 1983 to 2023.

Ostriches can be utilized as multipurpose animals suitable for producing meat, eggs, feathers, and leather. This growing interest in ostrich farming leads to an increased demand for comprehensive information on their management. But, little attention is paid to the consequences for their welfare. The study aimed to perform a research literature analysis on ostriches' welfare using the text mining (TM) and topic analysis (TA) methods. It identifies prevailing topics, summarizes their temporal trend within the last forty years, and highlights potential research gaps. According to PRISMA guidelines, a literature exploration was achieved using the Scopus® database, retaining keywords about ostriches' welfare. Papers distributed in the English language from 1983 to 2023 were included. Descriptive statistics, TM, and TA were applied to a total of n. 122 documents included. The findings revealed an increasing trend in research records since 1994. TM recognized the terms with the highest weighted frequency and TA identified the main topics of the research area, in the following order: "health and management", "feeding and nutrition", "welfare reproduction", "egg production", and "welfare during transport". The study confirms the increased focus on ostriches' welfare but shows that further studies are required to ensure the welfare of this species.

AI in Surgery: Navigating Trends and Managerial Implications Through Bibliometric and Text Mining Odyssey.

Background:This research employs bibliometric and text-mining analysis to explore artificial intelligence (AI) advancements within surgical procedures. The growing significance of AI in healthcare underscores the need for healthcare managers to prioritize investments in this technology. Purpose:To assess the increasing impact of AI on surgical practices through a comprehensive analysis of scientific literature, providing insights that can guide managerial decision-making in adopting AI solutions.Research Design:The study analyzes over 6000 scientific articles published since 1990 to evaluate trends and contributions in the field, informing managers about the current landscape of AI in surgery.Study Sample:The research focuses on publications from various influential publishers across North America, Northern Asia, and Eastern & Western Europe, highlighting key markets for AI implementation in surgical settings.Data Collection and Analysis:A bibliometric approach was utilized to identify key contributors and influential journals. At the same time, text-mining techniques highlighted significant keywords related to AI in surgery, aiding managers in recognizing essential areas for further exploration and investment.Results:The year 2022 marked a significant upsurge in publications, indicating widespread AI integration in healthcare. The U.S. emerged as the foremost contributor, followed by China, the UK, Germany, Italy, the Netherlands, and India. Key journals, such as Annals of Surgery and Spine Journal, play a crucial role in disseminating research findings, serving as valuable resources for managers seeking to stay informed.Conclusions:The findings underscore AI's pivotal role in enhancing diagnostic precision, predicting treatment outcomes, and improving operational efficiency in surgical practices. This progress represents a significant milestone in modern medical science, paving the way for intelligent healthcare solutions and further advancements in the field. Healthcare managers should leverage these insights to foster innovation and improve patient care standards.

Visualized analysis of microscale rock mechanism research: A bibliometric data mining approach

Rock mechanics is an indispensable discipline in diverse sectors, from resource retrieval to disaster mitigation. Diving deeper into this field, particularly into microscale rock mechanics, offers strategic insights and potential advancements for rock engineering practice. The objective of this research is to map the scientific production tied to microscale rock mechanics to date. In doing so, we perform a bibliometric analysis to look over and discuss the performance of the related literature. The conceptual fabric of microscale rock mechanics research, constituted by four central themes, was revealed and visualized through a text mining analysis. These areas include (1) modeling and simulation of fluid flow and transport within porous media, (2) characterizing fracture and failure in rocks, (3) understanding the deformation mechanism in response to geological processes, and (4) studying the mechanical properties of rocks subjected to extreme conditions. Lastly, an upcoming research agenda for microscale rock mechanics was proposed, centered on addressing three identified research gaps: (I) the integration of geological processes to characterize mineral properties, (II) the augmentation of fracture predictions achieved through multiscale modeling of rock heterogeneity, and (III) the exploitation of Artificial Intelligence technologies for anticipating complex fracturing scenarios. This comprehensive approach promises to enrich our understanding of rock mechanics and its applications.

Augmented Reality and Virtual Reality: A New Way of Seeing the World

Technologies such as (AR) Augmented Reality &(VR) Virtual Reality, which provide immersive digital experiences, interactive environments, simulation, and engagement, have completely changed how we approach learning. However, in order to meet the huge demand in education, these technologies which are still in the emerging stage need to be heavily customized and heavily invested in. This thorough analysis seeks to contextualize the last few years of development of Virtual and Augmented Reality in the Education. For additional study, a total one thousand five hundred and thirty-six articles are chosen using text mining and theme analysis techniques. Based on earlier research on AR and VR in education, hypotheses were developed and are currently being processed and analysed to reveal the current development in literature via Augmented Reality and Virtual Reality, applications, benefits, and future directions. The findings show that wearable technology has contributed significantly to the exponential expansion in the use of Virtual and Augmented Reality in education in recent years. Results also highlight the need for faster adoption and customization of these technologies in educational institutions, based on secondary data. An increasing number of educational applications for the learning process are emerging as Virtual and Augmented Realityexp and quickly. It is advised that researchers stay up to date on the gaps in AR and VR’s Changeover to education &develop practical adaptation strategies to maximize the benefits of these technological development with significant developments in high-speed transmission and processing, AR &VR are developing as Display Platforms for Next Generation for more intimate human-digital interactions. Nonetheless, matching the extraordinary Human Vision Performance while keeping Near the Eye Display module tiny and lightweight presents unprecedented hurdles for optical engineering. Fortunately, new advances in Holographic Optical Elements HOEs and Lithography Enable Devices present novel approaches to overcoming these challenges in Virtual and Augmented Reality which would otherwise be problematic with traditional optics

Text Mining Analysis of Consumer Preferences for Products Across Age Groups in China

Text Mining Analysis of Consumer Preferences for Products Across Age Groups in China

A survey on the reasons why victims of stalking did not exhibit help-seeking behavior: a text-mining analysis.

Stalking can escalate into violent acts such as threatening and inflicting physical harm, posing a serious threat to personal safety. To prevent exacerbating stalking victimization, victims must seek help and report incidents to the police or relevant authorities. However, victims, in general, underreport these incidents to public institutions. Moreover, there is insufficient understanding of why victims of stalking, especially men, refrain from seeking help. Therefore, this study used text mining to explore the reasons victims of stalking in Japan do not seek help while considering the severity of victimization and analyzing data separately for men and women. Among 908 Japanese individuals who reported experiencing repeated stalking behavior from a former intimate partner in the past five years, 253 men and 321 women who did not consult public authorities were included in this study. Participants provided their experiences of being stalked by former romantic partners and were classified into stalking-only, threatened, and physical aggression victim groups based on their self-reported experiences in an online survey. Reasons for not seeking help were collected through open-ended questions and analyzed using text mining. A co-occurrence network analysis revealed that among men in the threatened victim group, the reason for not seeking help was the belief that their complaints would not be taken seriously. The physical aggression victim group did not seek help due to the perception that a female perpetrator does not pose a danger. Among women in the physical aggression victim group, concerns about provoking the perpetrator or worsening the situation by seeking help, as well as feelings of embarrassment, were reasons for not seeking assistance. The identification of gender stereotype-related reasons among male victims was a valuable insight that could only be obtained through comparison with female victims. However, the study was limited to addressing the individual characteristics of the cases, thus providing only hypothetical insights into general trends. In future research, it will be necessary to generate hypotheses from the findings of this study and accumulate hypothesis-testing research to develop effective strategies for promoting help-seeking behavior among stalking victims.

Gender Equality Research: A Bibliometric Analysis of Trends in Turkey

Gender disparity persists in both developed and developing nations, despite several attempts to achieve gender parity. This paper explores the evolution and importance of gender equality research, with a focus on Turkey, through bibliometric analysis. It also examines significant subjects, patterns, and academic contributions in the discussion of gender equality using a dataset of 12,539 publications from the fields of business, economics, and management published between 2000 and 2023. Advanced bibliometric methods such as text mining and social network analysis have revealed a discernible increase in gender-related publications over the last 20 years. The United States, the United Kingdom, and Sweden have all made significant contributions. The research provides a list of relevant research publications and keywords related to gender equality, women's representation, and gender differences in work. In addition, it highlights the departure from formal theories of equality and the shift towards more nuanced perspectives that consider the complex interplay among social, economic, and cultural factors. Coordinating gender equality with wider development agendas, particularly the Sustainable Development Goals (SDGs), is a crucial point of guidance for academics, practitioners, and policymakers, as the paper makes clear. In the twenty-first century, gender inequality poses many complicated problems that require interdisciplinary collaboration and continued research into understudied areas including the intersections of gender with other social identities.

Hotelling rule in non-renewable resources: A bibliometric and systematic literature review analysis

This research aimed to provide a comprehensive mapping of studies on the application of the Hotelling rule in non-renewable resources from 1970 to 2024, identifying the most prominent research topics and trends, key characteristics, evolution, and directions for future studies. To achieve this, the following research questions were addressed using a mixed-method approach, including bibliometric analysis, text mining, and content analysis: (i) How has research on the Hotelling rule in non-renewable resources evolved? (ii) What are the most relevant research topics and trends in Hotelling rule research? and (iii) What future directions should studies on the Hotelling rule in non-renewable resources pursue? A total of 197 journal articles extracted from the Scopus database were analyzed to map the main body of literature. Four main research clusters were identified: (1) theoretical and empirical perspectives on the Hotelling rule, (2) the Hotelling rule in non-renewable resource management, (3) economic policy and sustainability within the Hotelling framework, and (4) resource depletion and pricing under the Hotelling rule. Four key areas for future research were proposed, focusing on diversification to other non-renewable resources, evaluation of policies and geographical contexts, technological innovations and government policies, and sector-specific applications of the Hotelling rule. These directions are crucial for promoting sustainability in the management of non-renewable resources over time.