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This paper aims to solve the disadvantages of content-based domain ontology (CBDO) and metadata-based domain ontology (MDO) and improve organization and discovery efficiency of library resources by resource ontology (RO).

The paper constructed an RO model. Methods of informetrics are utilized to reveal semantic relationships among library resources. Methods of ontology, ontology-relational database mapping (O-R mapping) and relational database modelling are utilized to construct RO. Take author co-occurrence for example, the paper demonstrated the capability of RO model.

RO not only revealed the deep-level semantic relationships of metadata of library resources but also realized totally computer-automated processing. RO improved the efficiency of knowledge organization and discovery.

Semantic relationships revealed by RO are limited to simple metadata, which makes it difficult to reveal fine-grained semantic relationships. Ongoing research focuses on the revelation of semantic relationships based on the title and abstract.

The paper includes implications for utilizing methods of Informetrics to construct ontology.

This paper proposed a standardized process of ontology construction in library resources. It may be of potential interest for anyone who needs to effectively organize library resources.

This study aims to provide a holistic review of social media influencers (SMIs) research based on a unique approach of bibliometric analysis and content analysis between 2011 and 2020. The review examines the main influential aspects, themes and research streams to identify research directions for the future.

The sample selection and data collection were done from the Scopus database. The sample dataset was refined based on the inclusion and exclusion criteria to determine the final dataset of 183 articles. The dataset was exported in the BibTeX format and then imported into the BiblioShiny app for bibliometric analysis. The content analysis was done following the theory-context-methodology framework.

The several findings of this study include (1) Co-word analysis of most used keywords; (2) Longitudinal thematic evolution; (3) The focus of the research papers as per the theory-context-methodology review protocol are persuasion knowledge model, fashion and beauty industries, Instagram and content analysis, respectively; and (4) The network analysis of the research studies is known as the co-citation analysis and depicts the intellectual structure in the domain. This analysis resulted in four clusters of the research streams from the literature and two emergent themes (Chen et al., 2010)

In general, the previous reviews in the area are either domain, method or theory-based. Thus, this study aims to complement and extend the existing literature by presenting the overall picture of the SMI research with the help of a unique combined approach and further highlighting the trends and future research directions based on the findings of this study.

This paper aims to provide a comprehensive bibliometric analysis of the current state of social media literature by examining co-word network analysis and thematic keyword analysis of both scholars and hospitality and tourism journals in three sub-periods (2002-2006, 2007-2012 and 2013-2018).

This research used a bibliometric analysis of social media literature in the field of hospitality and tourism by synthesizing the literature of a large sample of 601 studies over an extended time period (2002-2018).

The jump in the number of examined contexts, platforms, methodological approaches and research implications during 2007-2012 has marked the start of social media as a new phenomenon in hospitality and tourism research. Interestingly, International Journal of Contemporary Hospitality Management was a leading contributor to social media research between 2017 and 2018. The period 2013-2018 has witnessed newly emerging trends such as “big data,” “e-tourism,” “green experience” and “smart tourism.” This study’s analysis indicated that few keywords in social media appeared in the maturity stage. New platforms such as “Expedia,” “Foursquare,” “Flickr,” “Pinterest,” “Couchsurfing” and “Twitter” appeared between 2013 and 2018.

The scope of past research on the evolution of social media was limited to either a few of the most popular cited journals and/or analysis within a narrow time span. In contrast, the present study aims to uncover the rapid progress in social media research between 2002 and 2018, addressing growth in breadth and depth of thematic areas. Finally, this paper concluded with the proposal of knowledge-based life cycle framework that identifies key themes related to social media research. This framework provided insights into what has been addressed in previous literature (maturity and decline stages) and reported the topics that have been under-researched (introduction and growth stages).

The research work provides a comprehensive bibliometric analysis on blockchain in general and with respect to trust and reputation management in particular. The research work also incorporates the research progress in Pakistan in the field of blockchain.

The research study is conducted in three phases in which 9 different research questions are assessed for the time duration of 2012–2020 on a total of 9,314 published studies. The source of the research study is from one of the most prestigious databases, the Web of Science (WoS). The scholarly publication includes analysis on WoS categories, annual publication trends, types of documents, research areas, and collaboration network amongst countries, co-word analysis, top 10 countries and top 10 organizations with respect to research publications. The authors use VOSviewer tool to generate collaboration network of countries and co-occurrence network for co-word analysis. The connecting thread among the research question is the overarching research objective of exploring and understanding research out in blockchain. The authors have conducted the research in three phases. Phase 1 is planned to show various quantitative analysis of blockchain worldwide with respect to all 9 questions. In Phase II, prime importance is being given to the trust and reputation management aspect of blockchain. Phase III is concerned with the findings of 9 research questions with Pakistan as the ultimate focus.

Major findings include that China and the USA are the leading countries as they have contributed the most in research field of blockchain. Computer science emerged as the leading research area. The first research article dates back to 2013 with significant rise in publication trend over the last 4 years from 2017–2020. Trust management emerged as one of the key fields where blockchain plays a pivotal role. Pakistan occupies a position in top 20 countries with respect to research contribution. However, in order to rank amongst top 10 research countries, Pakistan needs rapid technological advancement. The immense rise in research publication trend in Pakistan from the year 2019–2020 as compared to prior 2019 era indicates that due focus is being given in the field of blockchain in Pakistan since the last two years.

The authors have considered WoS data source. Therefore, the study is limited to those published scholarly studies which are present in WoS database. More detailed assessment can be performed by analyzing other data resources. The authors have performed analysis based on 9 research questions. However, other parameters can also be included to perform more enhanced and detailed analysis. All types of documents are included in our research work including secondary studies also. However, some authors might not prefer to include all types of documents.

The paper includes implications for the development of trust and reputation management area of blockchain.

The bibliometric analysis is worthy for scholars, researchers and students to help them make better decision in the field of blockchain with respect to various parameters. The study also serves as a motivating factor to conduct research in the area of blockchain with any language as a medium of research.

The purpose of this paper is to understand the representation that senior managers of Italian social enterprises have about their organization’s intellectual capital (IC), precisely about the human capital, relational capital and organizational capital.

This paper used a qualitative approach. A total of 81 senior managers were interviewed individually. Interview data were analyzed using different techniques of content analysis, particularly by using the T-Lab software (analysis of word occurrence and co-word mapping, analysis of Markovian sequences).

Findings confirm the divide between theory and practice of IC. The representation of the IC dimensions is rather different from the definition that is found in the academic literature. Limited awareness about IC components and their generative power of knowledge determines a limited exploitation of the social enterprises’ organizational knowledge.

The group reached is limited to Italy and is not statistically representative of all Italian social enterprises.

Social enterprises are crucial in the development and well-being of societies. However, the findings suggest that many social enterprises managers are not fully aware of the importance of IC and how it may create value for their organizations. This paper stresses that senior managers of social enterprises need to, through various methods, have a better understanding of IC management and knowledge creation if they are to fully utilise the potential of IC in their organizations for survival and growth.

This is the first attempt to explore the perception of IC’s components among social enterprises, which represent an important development of non-profit organizations.

The purpose of this paper is to perform a thorough analysis of the literature on the parameters of sustainability of the micro-enterprises. It seeks to provide an organizing framework to identify research gaps and future directions. Using data from Web of Science and Scopus, the study offers insights into key trends, authorship and thematic shifts, informing future research design and positioning.

Researchers used a systematic review methodology, gathering data from Web of Science and Scopus databases. R Studio software facilitated bibliometric analysis. This study scrutinized research papers to construct an organizing framework and identify thematic trends in sustainability parameters for micro-enterprises.

The review presents a comprehensive overview of sustainability parameters in micro-enterprises, revealing significant research trends, key authors, countries and journals. It identifies gaps and suggests future research directions, aiding in the design and positioning of forthcoming studies in this domain.

Limitations may include the scope of databases accessed and potential biases in the selected literature. Future studies could explore additional databases or incorporate qualitative analyses for deeper insights into sustainability parameters in micro-enterprises.

This study offers practical insights for policymakers, practitioners and researchers by highlighting key sustainability parameters in micro-enterprises. It informs decision-making processes concerning resource allocation, policy formulation and support mechanisms for sustainable development.

Understanding sustainability parameters in micro-enterprises has significant social implications, particularly for vulnerable groups like craftsmen, women and young entrepreneurs. By addressing these parameters, interventions can enhance livelihoods and contribute to broader socio-economic development.

By providing a thorough analysis of sustainability factors in micro-enterprises and applying bibliometric analysis to shed light on research trends, this paper adds to the body of literature. Its organized framework identifies gaps and guides future research, offering value to scholars, policymakers and practitioners invested in sustainable development at the grassroots level.

This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.

The purpose of this article is to investigate the use of word co-occurrence analysis method in mapping of the scientific fields with emphasis on the field of Informetrics.

This is an applied study using scientometrics, co-word analysis and network analysis and its steps are summarised as follows: collecting the data related to the Informetrics field indexed in Web of Science (WOS) database, refining and standardising the keywords of the extracted articles from WOS and preparing a selected list of these keywords, drawing the word co-occurrence map in the Informetrics field and analysing of results.

Based on the resulted maps the concepts such as information science, library, bibliometric analysis, innovation and text mining are the most widely used topics in the field of Informetrics. The co-word occurrence maps drawn at different periods show the changes and stabilities in the concepts related to the field of Informetrics. A number of topics such as “bibliometric analysis” are present in all years, whereas others such as “innovation” have disappeared. New topics emerge as a recombination of existing topics and in interaction with new (technological) developments.

The results of these analytical studies can be used as a guide for determining research priorities in the scientific fields, and also for planning and management in academic institutions.

The purpose of this study is to identify the existing research themes and future directions of the FinTech field by analyzing the dynamics of co-word burst.

A dataset of 1792 SCI or SSCI articles retrieved from the Web of Science database. First, the paper conducted a scientific production analysis. Then, using bibliometric analysis, the paper conducts co-word-burst analyses for keywords, title, abstract and Keywords Plus to detect the emerging trends. Based on these trends, future research directions were forecasted.

The study detected six research themes: the knowledge of FinTech, FinTech applications, FinTech technologies, COVID-19, FinTech ecosystem and FinTech implications for research. These six FinTech research themes were further conceptualized as a six-dimensional analytical framework for FinTech investigations. Then, the study forecasts that these six themes and related conversations will be an ongoing focus of Fintech research, particularly COVID-19 effects on FinTech.

This study is the first attempt to review FinTech literature based on quantitative and qualitative analyses of co-word burst. It overcomes the limitation of individual/group determinant(s) studies and presents a holistic view of current research themes and future research directions in FinTech field.

This paper reviews the literature on the business models of small and medium-sized enterprises (SMEs). It seeks to examine the profile, conceptual and intellectual structure of the literature whilst leveraging the findings to suggest promising future paths to advance our knowledge on business models of SMEs.

The study resorts to a systematic literature review that conducts descriptive, bibliometric (i.e. co-word occurrence analysis and bibliographic coupling of documents analysis) and content analyses to review the literature on business models of SMEs. The research protocol included 301 articles collected in the Web of Science (WoS) database in the descriptive and bibliometric analyses. The bibliometric analysis was performed using the VOSviewer software.

The descriptive analysis portrayed the profile of this research stream. The systematisation of the co-word occurrence analysis describes the four clusters that comprise the conceptual structure of this research field. The content analysis of the bibliographic coupling of documents’ clusters portrays the seven clusters that involve the intellectual structure of this research area.

The integrated and holistic approach adopted in this study provides a detailed overview of the literature on business models of SMEs. We propose an integrative framework for the literature that bridges the main themes that form the conceptual and intellectual structure of this field of research. A comprehensive agenda for future research is suggested and implications for theory, policy and practice are stated.