Search results

The purpose of this study is to examine research on academic libraries and the social web published from July 1, 2019, to June 30, 2023.

The article search and filtering procedures mirrored those of Choi and Harper (2020) and Carlsson (2015), resulting in a total sample size of 93 articles. These articles underwent examination based on the same eight variables (i.e. journal outlet, research theme, publication year, social web type, method, keyword, study participant type and study country) as employed by Choi and Harper (2020) and Carlsson (2015), with the addition of two new variables (i.e. research purpose and the impact of COVID-19).

The research article volume has consistently maintained a stable trend. A notable difference from Choi and Harper (2020) and Carlsson (2015) is the rise of “user perspectives” as the second most prevalent theme. Unlike Choi and Harper (2020), the “survey” method is predominant. Many research purposes, excluding “marketing and promotion,” lack attention. Additionally, there’s a dearth of studies on the impact of COVID-19.

The findings from the study not only offer a snapshot of the current research landscape on academic libraries and their engagement with the social web but also offer insights for future scholarly endeavors.

There is a limited effort in exploring the recent literature regarding the role of the social web in academic libraries. This study serves as a valuable guide for contributing to this dynamic research stream and provides various up-to-date implications.

The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.

By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.

(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.

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.

This paper aims to check the fragmentation of knowledge across multiple sources of evidence, identifying, scrutinizing and outlining suggestions concerning the challenges researchers face when using multiple sources of data to identify studies.

This study produced a comprehensive database of 15,848 items from Scopus, Web of Science and EBSCO on the organizational growth and decline topics. The analyses carried out to check the fragmentation of scientific knowledge and the challenges in identifying studies have made use of the basic data frame functions in R’s language and the Bibliometrix and Corpus R’s packages.

This study confirms the fragmentation of scientific knowledge as well as it identifies the following challenges: missing information in key fields, nonexistence of standards in terminology, limitations on data extraction, duplicates and multiple formats of cited reference. Additionally, it suggests practical coping procedures and advances implications for stakeholders and an agenda for future research.

This study provides valuable and practical examples with empirical confirmation of scientific knowledge fragmentation and offers an integrated view of many challenges in the process of identifying studies. Moreover, by offering suggestions to address these challenges, this study not only offers a practical guide to scientific researchers but also initiates a wider discussion regarding knowledge organizing in social sciences.

The paper aims to provide an overview of the state-of-the-art of the event industry in the context of digitalization to understand how digital technologies change the event industry and what research topics are the most promising for further exploration.

A bibliometric analysis of the existing body of knowledge on the topic was conducted and the results were visualized using CiteSpace 5.8.R3. A total of 1999 articles and proceeding papers from the Web of Science Core Collection published between 2007 and 2022 were selected for our analysis. Based on the articles and proceeding papers in the Web of Science Core Collection database, we selected a set of publications for our analysis. The data were obtained through specific keywords related to our research topic. The method involves a process of three main stages: data collection, data processing and the bibliometric analysis.

Co-citation analysis indicated that issues of crowd management and tracking human mobility during mass events are important for the event industry and that technologies such as the Internet of Things, special-purpose mobile applications and systems make it easier for an event organizer to handle the issues. The findings demonstrated a weak scientific collaboration between countries in the topic studied and shift of research hotspots to study of satisfaction, motivation and behavioral patterns of events attendees. Based on this analysis, three directions for future research were revealed.

The results should be interpreted in light of our sample, because the analysis was conducted within our sample which has boundaries. We collected data from all categories in the Web of Science Core Collection database, but we considered only articles and proceeding papers as opposed to all possible types of scientific publications and other databases. In the study, we focused on detecting the state-of-the-art of the event industry in the context of digitalization overall. More specific topics that could be analyzed remain, for example, the dependency of digital technologies from the event type, etc.

This study reflects the state-of-the-art of the event industry in the context of digitalization. It provides researchers with key developmental trends in the event industry, which assists them in more deeply understanding the evolution of research hotspots in the field during last 15 years and defining future research agenda. The paper presents an overview of digital technologies used in various types of events and describes the issues and results related to the implementing digital technologies. The results obtained were extremely important, as they can be used by event managers and organizers to enhance customers’ experience during the events.

This study reflects the state-of-the-art of the event industry in the context of digitalization. This is the first attempt to make an overall analysis of scientific papers published in the Web of Science Core Collection on the topic studied without excluding any categories. The search procedure is transparent, and the results can be reproduced in other search fields using the same approach. Based on this analysis, three directions for future research were revealed including technological aspects of online event-based social networks, issues of crowd management and security at mass events and issues of attendees’ acceptance of novel digital technologies.

This study aims to examine the research output on digital divide from 2001 to 2020 and measure the qualitative and quantitative growth of literature during the stated period by using required bibliometric measures for identifying the types of documents, yearly growth, country productivity, citation network of collaborative countries, authorship pattern, top authors, cocitation networks and assorted facets.

Web of Science database was used to retrieve the required data for this study. Keeping the objectives of this study in mind, the keyword “Digital Divide” was used as the search term. Moreover, the retrieved data were limited from the year 2001 to 2020 for two decades. A total of 5,518 publications were filtered and focused for subsequent facet-wise analysis and interpretation. Required bibliometric indicators like types of documents, yearly growth, authorship pattern, degree of collaboration (DC), country productivity, h-index and citation impact were used to study various dimensions of publication trends. VOSviewer software was used to visualize the authorship network, bibliographic coupling and keyword occurrences.

This study finds a total of 5,518 publications on the topic digital divide contributed by 14,277 authors from 130 countries across the world published through 2,843 source titles in 13 global languages during the past two decades (2001–2020). The annual growth of publications (AGP) on the topic digital divide shows 38.43% AGP globally. Journal articles have been identified as the preferred type of document with 73.11% of the literature. The DC indicates a healthy trend of collaborative research with a mean value of 0.70. The USA is the table topper with the contribution of 1,933(35.03%) publications and 77 h-index and James J., from Tilburg University, The Netherlands, is identified as top amongst the most productive authors with the highest number of 34 publications (h-index 14).

This study restricts its scope on research productivity to the theme “digital divide” regarding authorship pattern, DC, most productive authors, most productive countries, most published sources and other key facets. This study exclusively refers to the Web of Science database in retrieving the required data. Moreover, this study takes global research into account with no geographical or language limitations and comprehends literature on digital divide for two decades ranging from the years 2001 to 2020.

Teachers and research scholars interested in bibliometric studies can benefit from insights into the scholarly documents published on the topic digital divide from 2001 to 2020.

This study yields some interesting findings on published literature on the digital divide during the past two decades relating to the most striking contributions, highly cited journals, the most prolific authors, country productivity, keyword cooccurrence and assorted parameters.

The purpose of this study is to review and synthesize the literature on in-app advertising, identify gaps and propose future research directions.

The authors use a systematic literature review (SLR) approach, following the PRISMA guidelines, to investigate the current state of research in in-app advertising. The study uses 44 shortlisted articles from the Scopus and Web of Science databases. Using the Theory-Context-Characteristics-Methodology (TCCM) framework, the authors analyze the gaps in theory, context, characteristics and methods.

Using thematic analysis, the authors identify five main themes in the in-app advertising literature, namely, ad platform optimization; mobile app user psychology and behavior; ad effectiveness; ad fraud; and security, privacy and other user concerns. The findings show the need for empirical research, with a strong theoretical foundation in emerging ad formats of in-app advertising, user behavior and buy-side of in-app advertising.

This is a maiden study to conduct a domain-based SLR in the emerging field of in-app advertising using the TCCM framework. The authors highlight the key differences between in-app advertising and mobile web advertising. The authors propose theories in the advertising field that could be used in future empirical studies of in-app advertising.

El propósito de esta investigación es revisar y sintetizar la literatura sobre la publicidad en Apps, identificar lagunas y proponer futuras direcciones de investigación.

Utilizamos un enfoque de revisión sistemática de la literatura, siguiendo las directrices PRISMA, para investigar el estado actual de la investigación en publicidad en aplicaciones. El estudio utiliza 44 artículos preseleccionados de las bases de datos Scopus y Web of Science (WoS). Utilizando el marco Teoría-Contexto-Características-Metodología (TCCM), analizamos las lagunas en teoría, contexto, características y métodos.

Mediante un análisis temático, identificamos cinco temas principales en la literatura sobre publicidad en aplicaciones, a saber: optimización de plataformas publicitarias; psicología y comportamiento de los usuarios de aplicaciones móviles; eficacia publicitaria; fraude publicitario; seguridad, privacidad y otras preocupaciones de los usuarios. Nuestros hallazgos muestran la necesidad de investigación empírica, con una sólida base teórica en los formatos publicitarios emergentes de la publicidad en Apps, el comportamiento del usuario y el buy-side de la publicidad en Apps.

Se trata de un estudio pionero para realizar una revisión sistemática de la literatura basada en el dominio en el campo emergente de la publicidad en Apps utilizando el marco TCCM. Destacamos las principales diferencias entre la publicidad en aplicaciones y la publicidad en la web para móviles. Proponemos teorías en el campo de la publicidad que podrían utilizarse en futuros estudios empíricos sobre la publicidad en Apps.

本研究旨在回顾和总结有关应用内广告的文献, 找出差距并提出未来的研究方向。

我们采用系统性文献综述方法, 遵循 PRISMA 指南, 调查应用内广告的研究现状。研究使用了 Scopus 和 Web of Science (WoS) 数据库中的 44 篇入围文章。利用理论-背景-特征-方法（TCCM）框架, 我们分析了理论、背景、特征和方法方面的差距。

通过主题分析, 我们确定了应用内广告文献的五大主题, 即广告平台优化; 移动应用用户心理和行为; 广告效果; 广告欺诈; 安全、隐私和其他用户关注点。我们的研究结果表明, 有必要在应用内广告的新兴广告形式、用户行为和应用内广告买方等方面开展实证研究, 并奠定坚实的理论基础。

这是一项首次使用 TCCM 框架对新兴的应用内广告领域进行基于领域的系统性文献综述的研究。我们强调了应用内广告与移动网络广告的主要区别。我们提出了广告领域的理论, 可用于未来的应用内广告实证研究。

Existing tourism review articles have limited review topics and cover a relatively short period. This review paper aims to extend the coverage of the previous literature and enhances the completeness of tourism-related studies to provide comprehensive tourism-related literature from 1945 (World War II onward) to 2022. Specifically, this paper reveals the major research themes present in published tourism research during this time period and highlights the evolution of tourism research from the preliminary phase, the transversal phase, to the growth phase.

The present study visualizes tourism research through networks of coauthors and their countries and regions, cocitation analysis of keywords and explores the thematic evolution of tourism research after the World War II (i.e., 1945–2022) from Web of Science and Google Scholar through bibliometric analysis.

Findings reveal that the themes of tourism research in the past years can be divided into seven major research themes. The tourism research evolution from World War II to 2022 can be categorized into three stages: preliminary (1945–1970), transversal (1971–2004) and growth (2005–2022). In addition, the research themes of tourism are not static but evolve according to the dynamics of the society and the industry, and that seven main research themes have been formed, namely, “heritage tourism,” “medical tourism,” “adventure tourism,” “dark tourism,” “sustainable tourism,” “rural tourism” and “smart tourism.”

The present study expands and refines the comprehensive literature in tourism research, as well as reveals the trends and dynamics in tourism research through network analysis and thematic evolution research methods.

现有的旅游评论文章在审查主题方面有限, 并且涵盖的时间相对较短。本综述文章扩展了先前文献的涵盖范围, 增强了与旅游相关研究的完整性, 提供了从1945年（第二次世界大战之后）到2022年的全面旅游相关文献。具体而言, 本文揭示了此期间发表的旅游研究中的主要研究主题, 并突出了旅游研究从初步阶段、横向阶段到增长阶段的演变。

本研究通过共同作者及其国家的网络、关键词的共同引用分析, 将旅游研究可视化, 并探索二战后旅游研究的主题演变。本研究通过文献计量学分析, 将 Web of Science (WoS) 和 Google Scholar 中的旅游研究（即 1945–2022 年）可视化。

研究结果显示, 过去几年的旅游研究主题可分为七大研究主题。从第二次世界大战到 2022 年的旅游研究演变可分为三个阶段：初步阶段（1945–1970 年）、横向阶段（1971–2004 年）和成长阶段2005–2022 年）。此外, 旅游的研究主题并不是静态的, 而是根据社会和行业的动态而演变, 形成了七个主要研究主题, 即“遗产旅游”、“医疗旅游”、“冒险旅游”、“黑暗旅游”、“可持续旅游”、“乡村旅游”和“智慧旅游”。

本研究通过网络分析和主题演变研究方法扩展和完善了旅游研究方面的综合文献, 并揭示了旅游研究的趋势和动态。

Los artículos de revisión existentes sobre turismo tienen temas de revisión limitados y cubren un periodo relativamente corto. Este artículo de revisión amplía la cobertura de la bibliografía anterior y mejora la exhaustividad de los estudios relacionados con el turismo para ofrecer una bibliografía exhaustiva sobre el turismo desde 1945 (Segunda Guerra Mundial en adelante) hasta 2022. En concreto, este documento revela los principales temas de investigación presentes en la investigación turística publicada durante este periodo de tiempo y destaca la evolución de la investigación turística desde la fase preliminar, la fase transversal, hasta la fase de crecimiento.

El presente estudio visualiza la investigación turística a través de redes de coautores y sus países y regiones, análisis de co-citación de palabras clave, y explora la evolución temática de la investigación turística después de la Segunda Guerra Mundial (es decir, 1945–2022) a partir de Web of Science y Google Scholar mediante análisis bibliométricos.

Los resultados revelan que los temas de la investigación turística de los últimos años pueden dividirse en siete grandes temas de investigación. La evolución de la investigación turística desde la Segunda Guerra Mundial hasta 2022 puede clasificarse en tres etapas: preliminar (1945–1970), transversal (1971–2004) y de crecimiento (2005–2022). Además, los temas de investigación del turismo no son estáticos, sino que evolucionan según la dinámica de la sociedad y de la industria, y que se han formado siete temas principales de investigación, a saber: “turismo patrimonial”, “turismo médico”, “turismo de aventura”, “turismo oscuro”, “turismo sostenible”, “turismo rural” y “turismo inteligente”.

El presente estudio amplía y perfecciona la amplia bibliografía existente en el campo de la investigación turística, además de revelar las tendencias y la dinámica de la investigación turística mediante el análisis de redes y los métodos de investigación de evolución temática.

The purpose of this study is to conduct a bibliometric analysis to discover the published information on the subject of “Library Automation Software.”

This study is based on bibliometric research to analyze the growth of literature on the subject area “Library Automation Software.” The data were retrieved from the leading database Web of Science to analyze the scholarly publications on the topic during 2001–2022. To analyze the bibliometric data on the subject, the VOSviewer, Biblioshiny and MS Excel software were used.

Results manifest that the topic of “Library Management Systems” has been greatly used by several authors as a title to publish their research work. The USA emerged as the most productive country. The most used keywords to retrieve literature on the topic were “Library Automation,” “Library Management Systems,” “KOHA,” “Integrated Library Systems” and “Open Source Software.”

To the best of the authors’ knowledge, this is the first bibliometric study in Pakistan that has been conducted to measure the productivity of literature at the international level on library automation.

Cyberbullying has become one of the reasons behind the increase in psychological and medical problems. A need to prevent recurrences of cyberbullying incidents and discourage bullies from further bullying the victims has risen. This problem has attracted the attention of all stakeholders across the globe. Various researchers have developed theories and interventions to detect and stop bullying behavior. Previously, researchers focused on helping victims, but as the times have changed, so has the focus of researchers. This study aims to analyze scientific research articles and review papers to understand the development of the knowledge base on the topic.

This study analyzes the performance of literature on cyberbullying perpetration (CBP) using the widely accepted bibliometric analysis techniques: performance analysis and science mapping. The study is based on a dataset extracted from the Web of Science database. Initially, 2,792 articles between 2007 and 2022 were retrieved, which were filtered down to 441. The filter was based on various criteria, but primarily on CBP. VOSViewer and MS Excel were used to analyze the data. In addition, VOSViewer was used to create “bibliometric citations, co-citations, and co-word maps.”

The findings include publication and citation quantum and trends, the top 20 active countries, the most significant research articles and leading journals in this domain. Major themes or clusters identified were “Cyberbullying and victim behavior,” bullying behavior, adolescents and intervention, “cyberbullying associations,” and “cyberbullying personality associations.”

The study is unique because it analyses research articles based on cyberbullies, whereas past studies explored only the victims' side. Further, the present study used the Web of Science database, whereas most studies use the Scopus database.