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Zakat during the COVID-19 outbreak has played a vital role and has been significantly discussed in the virtual environment. Such information about zakat in the virtual world creates unstructured data, which contains important information and knowledge. This paper aims to discover knowledge related to zakat administration during the pandemic from the information in a virtual environment. Furthermore, the discussion is contextualised to the socio-economic debates.

This is a qualitative study operated via text mining to discover knowledge of zakat administration during the COVID-19 pandemic. The National Board of Zakat Republic of Indonesia (BAZNAS RI) is selected for a single case study. This paper samples BAZNAS RI’s situation report on COVID-19 from its virtual website. The data consists of 40 digital pages containing 19,812 characters, 3,004 words and 3,003 white spaces. The text mining analytical steps are performed via RStudio. The following R packages, networkD3, igraph, ggraph and ggplot2 are used to run the Latent Dirichlet Allocation (LDA) for topic modelling.

The machine learning analysis via RStudio results in the 16 topics associated with the 3 primary topics (i.e. Education, Sadaqah and Health Services). The topic modelling discovers knowledge about BAZNAS RI’s assistance for COVID-19 relief, which may help the readers understand zakat administration in times of the pandemic from BAZNAS RI’s virtual website. This finding may draw the theory of socio-economic zakat, which explains that zakat as a religious obligation plays a critical role in shaping a Muslim community's social and economic processes, notably during the unprecedented times of COVID-19.

This study uses data from a single zakat institution. Thus, the generalisation of the finding is limited to the sampled institution.

This research is both theoretically and practically important for academics and industry professionals. This paper contributes to the novelty in performing text mining via R in gaining knowledge about the recent zakat administration from a virtual website. The finding of this study (i.e. the topic modelling) is practically essential for zakat stakeholders to understand the contribution of zakat in managing the COVID-19 impacts.

This work derives a theory of “socio-economic zakat” that explains the importance of a zakat institution in activating zakat for managing socio-economic issues during the pandemic. Thus, paying zakat to an authorised institution may actualise more maslahah (public interest) compared to paying it directly to the asnaf (zakat beneficiaries) without any measurement

This study is among the pioneers in gaining knowledge from Indonesia’s zakat management during the COVID-19 outbreak via text mining. The authors’ way of analysing data from the virtual website using RStudio can advance Islamic economics literature.

Foresight J's journey started in 1999, and in 2022, it marked the conclusion of its 24 years of publication. This paper aims to provide an overall overview of important research trends published in Foresight J between 1999 and 2022 by conducting a quantitative analysis of the journal’s literature. The overarching goal is to provide valuable insights into the dynamics of scholarly communication, aiding researchers, institutions and policymakers in assessing the significance and influence of academic work, guiding future research directions and academic evaluation.

The two bibliometrics methodologies that make up the methodology of this article are scientific mapping and performance analysis. Authors have explained the development and composition of the Foresight J using these methods. The SCOPUS database is being used in current research to analyse several dimensions, such as the evolution of publications by year, the most cited papers, core authors and researchers, leading countries and prolific institutions. Moreover, the conceptual structure, scope, burst detection and co-occurrence analysis of the journal are mapped using network visualization software such as VOSviewer, CiteSpace and RStudio.

With a strong track record of output over the years, Foresight J has continued to develop in terms of publications. It is determined that “Saritas” is the author with the greatest overall impact. However, according to SCOPUS bibliometric data, “Blackman” and “Richardson” are the authors with the greatest relevance in terms of the quantity of articles. In addition, it becomes apparent that the USA, Australia and the UK are very productive nations in terms of publications. The most popular fields of the journal have always been forecasting, foresight, scenario planning, strategic planning, decision-making, technology and sustainable development. These are also the author keywords that appear the most frequently. In contrast, new study themes in the Foresight J include digital technologies, innovation, sustainability, blockchain, artificial intelligence and sustainability.

Several noteworthy research implications are provided by the bibliometric study of Foresight J. “Saritas” is the author with the most overall impact, indicating that the precise contributions and influence of this researcher in the fields of forecasting, foresight and related fields. Given that “Blackman” and “Richardson” are well-known writers, it is also critical to examine the scope and complexity of their contributions to potentially identify recurring themes or patterns in their writing. The geographic productivity results, which show that the USA, Australia and the UK are the top three countries for Foresight J publications, may encourage more research into regional differences, patterns of collaboration and the worldwide distribution of research endeavours in the context of forecasting and foresight. Popular fields including scenario planning, forecasting, foresight and sustainable development are consistent, indicating persistent research interests. Examining the causes of these subjects’ ongoing relevance can reveal information about the consistency and development of scholarly interests over time.

Foresight J’s bibliometric analysis has real-world applications for many stakeholders. It helps editors and publishers make strategic decisions about outreach and content by providing insights regarding the journal’s influence. Assessing organizational and author productivity helps institutions allocate resources more effectively. Policymakers acquire an instrument to evaluate research patterns and distribute funds efficiently. In general, bibliometric study of a journal helps decisionmakers in academic publishing make well-informed choices that maximize the potential of options for authors, editors, institutions and policymakers.

The societal ramifications of bibliometrically analysing Foresight J from 1999 and 2022 are substantial. This analysis highlights, over the past 24 years, research trends, technological developments and societal priorities have changed by methodically looking through the journal’s articles. Gaining knowledge about the academic environment covered by the journal can help raise public awareness of important topics and promote critical thinking. In addition, the analysis can support evidence-based decision-making by alerting decision makers to the influential research that was published in Foresight J. This could have an impact on the course of policies pertaining to innovation, technology and societal development.

This study presents a first comprehensive article that provides a general overview of the main trends and patterns of the research over the Foresight J’s history since its inception. Also, the paper will help the scientific community to know the value and impact of Foresight J.

This article offers a bibliometric analysis and explores the relationships among the documents on ecopreneurship by using relational techniques. The results highlight the publication trends; most cited documents, top contributing authors, countries and institutions with highest productivity and most contributing journals to the research field.

Initially, 216 documents were retrieved from the Thompson Reuters Web of Science Core Collection database with three document types: articles, review and book review. All the documents were considered for the analysis. Then VOSviewer and bibliometric analysis using R with an inbuilt utility Biblioshiny were used together for co-word analysis, co-citation network analysis, generating collaboration networks and also generating a unique three-field plot to analyze the evolution of a research field.

The results highlight the publication trends: most cited documents, top contributing authors, countries and institutions with highest productivity and most contributing journals to the research field. The network analysis of co-authorship, co-citation, keyword co-occurrence and bibliographic coupling reveals most prominent relationships between authors, documents, co-cited references, sources and countries for the available documents on the research field.

The study helps not only in expansion of knowledgebase on the research topic but also in understanding the evolution of the ecopreneurship to provide research support further in this area.

Ecopreneurship is an emerging field of research connecting ecology and entrepreneurship together, making it a potential research area. The contributions made to this research field from 1989 to 2019 serve as a core for conducting this analysis. The study is an effort to help in coordinating research network across countries, authors and affiliating universities.

The Journal of Accounting in Emerging Economies (JAEE), established in 2011, aims to publish research on contemporary accounting issues in emerging economies. This study used the bibliometric and scientometric approaches to provide deeper insights into the journal performance, prominent topics, author's contributions and citation structure. Content analysis was conducted to provide insights on the major themes addressed in JAEE.

This study analyses data from the Scopus database, Google Scholar and Journal website. The total number of documents analysed are 190. This study employs VOSviewer and RStudio to conduct the analysis which is categorised into four major parts: General performance indicators, citation structure, network analysis and content analysis.

Since JAEE commenced publication in 2011 and indexed in the Scopus in 2018, it achieved a 14.47% annual growth rate in document publication. It is encouraging to note that 88.4% of published documents were cited. In terms of total publication, the top contributing country is Malaysia; the USA is the primary contributor in citations. Five key themes emerged from the content analysis namely, international standards and earnings quality; audit quality and IFRS practices in emerging economies; corporate governance; financial reporting and earnings management; corruption and accounting disclosure; and ownership structure and firm performance.

This study offers a comprehensive assessment to the journal stakeholders about the past and current journal performance besides future trends and perspectives. Additionally, JAEE readers can gain insight into the nature of academic contributions in JAEE from 299 authors of 273 affiliated institutions in 67 countries.

Websites, search engines, recommender systems, artificial intelligence and digital libraries have the potential to support serendipity for unexpected interaction with information and ideas which would lead to favored information discoveries. This paper aims to explore the current state of research into serendipity particularly related to information encountering.

This study provides bibliometric review of 166 studies on serendipity extracted from the Web of Science. Two bibliometric analysis tools HisCite and RStudio (Biblioshiny) are used on 30 years of data. Citation counts and bibliographic records of the papers are assessed using HisCite. Moreover, visualization of prominent sources, countries, keywords and the collaborative networks of authors and institutions are assessed using RStudio (Biblioshiny) software. A total of 166 papers on serendipity were found from the period 1989 to 2022, and the most influential authors, articles, journals, institutions and countries among these were determined.

The highest numbers of 11 papers were published in the year 2019. Makri and Erdelez are the most influential authors for contributing studies on serendipity. “Journal of Documentation” is the top-ranking journal. University College London is the prominent affiliation contributing highest number of studies on serendipity. The UK and the USA are the prominent nations contributing highest number of research. Authorship pattern for research on serendipity reveals involvement of single author in majority of the studies. OA Green model is the most preferred model for archiving of research articles by the authors who worked on serendipity. In addition, majority of the research outputs have received a citation ranging from 0 to 50.

To the best of the authors’ knowledge, this paper may be the first bibliometric analysis on serendipity research using bibliometric tools in library and information science studies. The paper would definitely open new avenues for other serendipity researchers.

This study aims to analyse the nature and trends in the knowledge discovery process on COVID-19 and food insecurity using a comprehensive bibliometric analysis based on the indexing literature in the Scopus database.

Data were extracted from Scopus using the keywords COVID-19 and food security to ensure extensive coverage. A total of 840 research papers on COVID-19 and food security were analysed using VOSviewer and RStudio software.

The findings of the bibliometric analysis in terms of mapping of scientific research across countries and co-occurrence of research keywords provide the trends in research focus and future directions for food insecurity research during times of uncertainty. Based on this analysis, the focus of scientific research has been categorised as COVID-19 and food supply resilience, COVID-19 and food security, COVID-19 and public health, COVID-19 and nutrition, COVID-19 and mental health and depression, COVID-19 and migration and COVID-19 and social distancing. A thematic map was created to identify future research on COVID-19 and food security.

This analysis identifies potential research areas such as food supply and production, nutrition and health that may help set future research agendas and devise policy supports for better managing food insecurity during uncertainty.

This analysis provides epistemological underpinnings for knowledge generation and acquisition on COVID-19 and food insecurity.

This article aims to know the direction of current research based on the previous research in the last ten years (2012–2021).

Text mining was integrated with a network and content analysis as part of the mix methodological approach. The scientific articles, on the other hand, were assembled on Litmaps through web scraping. This process selected 86 articles about medical tourism published between 2012 and 2021. This study employed AntConc, RStudio and Gephi tools for data analysis and visualization.

A total of 138 articles were identified through Litmaps using web scraping and 86 studies met the criteria. The trend of medical tourism research is a positive sign for tourism and health industries; this is the beginning to recognize the importance of elaborating on these two topics. Several researchers have frequently studied issues of destination, hospital, development, quality, stakeholders, surgery, service, economics and policy. Policymakers must establish a medical tourism ecosystem to accommodate all stakeholders in this industry. This study also recommends focusing on supply and institution for medical tourism future research.

This literature review presents research trends on medical tourism in 2012–2021 based solely on articles available on the Litmaps search engine. If the time span is extended and the sources of articles are expanded there will be more literature available for analysis. The articles obtained are also only articles published in English due to the language limitations of the author.

Policymakers must establish a medical tourism ecosystem to accommodate all stakeholders in this industry. Stakeholders must work together to provide medical tourism package therefore people can get their health services while visiting available tourist areas.

The literary study of medical tourism over 10 years is considered the most recent systematic literature review.

The study aims to carry out predictive modeling based on publicly available COVID-19 data for the duration April 01, 2020 to June 20, 2020 pertaining to India and five of its most infected states: Maharashtra, Tamil Nadu, Delhi, Gujarat and Rajasthan.

The study leverages the susceptible, infected, recovered and dead (SIRD) epidemiological framework for predictive modeling. The basic reproduction number R0 is derived by an exponential growth method using RStudio package R0. The differential equations reflecting the SIRD model have been solved using Python 3.7.4 on the Jupyter Notebook platform. For visualization, Python Matplotlib 3.2.1 package is used.

The study offers insights on peak-date, peak number of COVID-19 infections and end-date pertaining to India and five of its states.

The results subtly indicate toward the amount of effort required to completely eliminate the infection. It could be leveraged by the political leadership and industry doyens for economic policy planning and execution.

The emergence of a clear picture about COVID-19 lifecycle is impossible without integrating data science algorithms and epidemiology theoretical framework. This study amalgamates these two disciplines to undertake predictive modeling based on COVID-19 data from India and five of its states. Population-specific granular and objective assessment of key parameters such as reproduction number (R0), susceptible population (S), effective contact rate (ß) and case-fatality rate (s) have been used to generate a visualization of COVID-19 lifecycle pattern for a critically affected population.

The main focus of the present study was threefold. Firstly, extraction of the data from the Library and Information Science (LIS) Links; secondly, pre-process the data to remove noises on maximum parameters; and lastly, to know the polarity of the discussion posted on LIS Links.

The advancement in the internet and Web 2.0 technologies have facilitated the academic community with many online platforms like Q&A sites, mailing lists, discussion forums, etc. for disseminating or seeking information. LIS Links is one such discussion forum commonly used by Indian LIS professionals. The analysis of these discussions can help in knowing the experience of LIS professionals in different aspects. The present study is based on a lexicon-based approach, which works on the bag of word model. The open source environment R and its different packages were used for the analysis.

The analysis shows that the majority of the posts on LIS Links were discussed with positive sentiments. There were only very few words of negative sentiments on the discussion forum of LIS Links.

The above review of the literature shows that there have been many studies in different domains. The user responses on different platforms were explored. Also, some studies have conducted sentiment analysis in LIS. However, this was limited to content posted by the libraries or the reviews of books. No research was found in the published literature on the analysis of the opinion of LIS professional.

This study aims to examine the research productivity and network visualisation on reproductive health (RH) domain with several bibliometric indicators and applied visualisation approach in co-authorship, citation, co-occurrence of keywords and bibliographic coupling analysis in the area of RH.

This study used bibliometric indicators to determine the highly productive authors, source title, documents and organisations. This study used Web of Science database and retrieved a total of 18,186 scientific publications on the domain of RH published during the period of 2010–2020. Data analysis was also performed using VOS viewer software and RStudio.

The findings discovered the increasing trends of research publications in reproductive health in past ten years. The USA UK, China and Australia were the top four productive countries in terms of publishing research in the arena, and “Kishsin DM” and “Hauser R” have secured in top two positions under highly prolific authors category. University of California, Harvard University and University of London were observed under the top three productive institutions in the domain. This study also revealed association and collaboration among authors, country and institutions in the visualisation analysis. The core findings of co-occurrence of keywords emphasised that “RH,” “assisted reproductive technology,” “women,” “pregnancy” and “in-vitro fertilization” were established frequently used keywords and have robust link strength.

The findings will be helpful to the researchers to know about the status of latest trends and development of the domain. This study is also helpful to the library authority for collection development in the specific subject domain.

To the best of the authors’ knowledge, there was no past study found on the evaluation of research productivity and network visualisation in the domain of RH, which is a globally important issue.