Bibliometric analysis to identify an emerging research area: Public Relations Intelligence—a challenge to strengthen technological observatories in the network society

Organizational learning and innovation: A bibliometric analysis and future research agenda

Organizational learning and innovation research have received increasing attention from researchers in recent years. However, there is a need to understand the research development of this topic and its trends. Therefore, this study aims to provide a comprehensive view of this field by conducting a bibliometric analysis of 773 research articles published over the past 41 years. The study identifies the journals, researchers, countries, institutions, and references in terms of productivity, citations, co-citations, common keywords, and their developments over three periods using the VOS viewer software. The results show a strong connection between organizational learning and organizational innovation. The number of publications related to organizational learning and innovation has continuously increased. The United States of America (USA) ranked first, contributing 21.86 % of the total publications. Additionally, the "Universidad de Granada" has been ranked first in overall publication output (16 publications, 2.07 %). The focus of researchers in this field has expanded to include different and new topics such as innovation performance and ambidexterity. The results of this paper may help academics and practitioners better understand research development trends and hotspots in the field of organizational learning and innovation and provide a comprehensive view of future research.

Digital Leadership: A Bibliometric Analysis

Digital disruption has changed organizations in an unprecedented way. The thriving field of digital leadership is expanding fast and few retrospective studies on this evolution have been made so far. This study presents a bibliometric and network analysis combining both Scopus and Web of Science databases to provide fresh insights into the evolution of the digital leadership research field. This study is based on a review of 79 publications from 57 journals, published between 2000 and 2020. The newness of the topic and the range of journals in which it is published confirms that digital leadership has gained interest from several different areas. Bibliometric analysis provides a description of the research field identifying the leading publishing journals, affiliation statistics, and most influential authors and expressive publications in the research field. Network analyses identify keyword evolution over time, co-citation relationships, and research clusters. Content analysis is used to identify key topics in the field with attention paid to interrelations among them. A brief description of each paper in the dataset and its methodological approach is provided. The results suggest that the topic will continue to attract more research, as it has not yet entered its maturity stage. This paper contributes to the literature by analyzing the relationship between digital leadership and e-leadership. This study also identifies the most leading digital leadership capabilities for a fast-changing world. Limitations and future avenues are also discussed.

Breakthrough potential of emerging research topics based on citation diffusion features

This article uses the characteristics of citation curves in emerging research topics (ERTs) and combines them with the ERTs’ knowledge bases to draw conclusions by comparing their development patterns. The goal of this study is to enrich the toolset for predicting breakthroughs in scientific research. A set of multidimensional and practical bibliometric indicators is used to identify ERTs, to further identify the knowledge bases of ERTs and construct citation curves for both ERTs and their knowledge bases. The development trends of the citation curves of ERTs and their knowledge bases in different time periods are compared and analysed from two dimensions: knowledge transition and continuous growth. We use the field of stem cell research to test our method. Based on the outcome of the analysis, we can assess the breakthrough potential of ERTs. The stratification, transition and recent changes of the citation curve can be used as a basis for analysing and assessing the ERTs’ breakthrough potential. The combination of different citation diffusion patterns of ERTs and their knowledge bases can improve the effectiveness of identifying ERTs that can become breakthrough innovations.

Smart Services in Smart Cities: Insights from Science Mapping Analysis

Against the backdrop of the expanding debate on smart cities, the objective of this paper is to examine to what extent and to what end the connection between smart services and smart cities has been explored in the literature, and what to make of it. It is argued that smart services, including demand- and innovation-driven service development, constitute an essential part of the broad concept of smart city. Viewed in this way, smart services serve as one of the key levers through which smart cities grow, develop, and build their resilience. By placing the analysis in the broader context of the smart city as smart service system, this paper sheds light on the still underexplored fields of research and suggests how they could be examined. For the purpose of the analysis, the Science Mapping (SciMat) method is employed as it allows to quantify and to visualize research output featured in Scopus and Web of Science (WoS), thus aiding the analysis. The added value of this paper is two-fold, i.e., (i) the SciMat analysis identifies the key dimensions of the nascent smart services in smart cities debate, and consequently, (ii) allows for suggesting topics that should be further investigated to detect the drivers for cities’ growth, resilience, and sustainability.

Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study

The study of the dynamics or the progress of science has been widely explored with descriptive and statistical analyses. Also this study has attracted several computational approaches that are labelled together as the Computational History of Science, especially with the rise of data science and the development of increasingly powerful computers. Among these approaches, some works have studied dynamism in scientific literature by employing text analysis techniques that rely on topic models to study the dynamics of research topics. Unlike topic models that do not delve deeper into the content of scientific publications, for the first time, this paper uses temporal word embeddings to automatically track the dynamics of scientific keywords over time. To this end, we propose Vec2Dynamics, a neural-based computational history approach that reports stability of k-nearest neighbors of scientific keywords over time; the stability indicates whether the keywords are taking new neighborhood due to evolution of scientific literature. To evaluate how Vec2Dynamics models such relationships in the domain of Machine Learning (ML), we constructed scientific corpora from the papers published in the Neural Information Processing Systems (NIPS; actually abbreviated NeurIPS) conference between 1987 and 2016. The descriptive analysis that we performed in this paper verify the efficacy of our proposed approach. In fact, we found a generally strong consistency between the obtained results and the Machine Learning timeline.

Research on polycystic ovary syndrome: a bibliometric analysis from 2009 to 2019

Polycystic ovary syndrome (PCOS) is a common reproductive and endocrine disease. However, there have not been any bibliometric studies on the latest scientific results and research trends of PCOS. This study aimed to review the state of research in PCOS worldwide. Publications on PCOS from 2009 to 2019 were identified and evaluated from the database Web of Science. A total of 7814 articles were retrieved. Shanghai Jiao Tong University published the most articles, with 218 publications. Gynecol Endocrinol had the greatest number of publications (n = 541). J Clin Endocr Metab was cited the most, with a total of 32,207 times. An article written by March et al. in 2010 had the most global citations (737 times) and local citations (463 times). From 2009 to 2019, the number of PCOS global publications gradually increased. Gynecol Endocrinol and Endocr Metab were popular journals for PCOS research. Research trends gradually shifted from treatment and methodology to genetics and basic research. The terms 'microrna,' 'rt qpcr,' 'lncrna,' and 'histological examination' may be hotspots that should be focused on in PCOS research.

An exploratory study of the all-author bibliographic coupling analysis: Taking scientometrics for example

All-author bibliographic coupling analyses (AABCA) take all authors of the article into account when constructing author coupling relationships. Taking scientometrics as an example, this article takes the papers from 2010 to 2019 as data sample and divides them into two periods (limited to 5 years) to discuss the performance of AABCA in discovering potential academic communities and intellectual structure of this discipline. It is found that when all authors of the paper are considered, the relationship between the bibliographic coupling authors presents a certain regularity and the bibliographic coupling is likely to be passed between different pairs of authors. With the transitivity of the coupling relationship, AABCA can effectively identify and discover the potential academic groups of this discipline, and more fully reflect the degree of cooperation among authors. AABCA is an effective method to reveal the intellectual structure in the field of scientometrics, and it is easier to find some small research topics with weak correlation. In addition, AABCA is also an ideal way to explore the author’s research interests over time.

A systematic investigation on the research publications that have used the medical expenditure panel survey (MEPS) data through a bibliometrics approach

Purpose

This study aimed to examine how Medical Expenditure Panel Survey (MEPS) data have been used to support scientific discoveries in biomedical and health sciences, and provide insight to researchers who are interested in using MEPS regarding collaborations and dissemination of research output.

Design/methodology/approach

A bibliometric approach was used to systematically examine the publications that used MEPS data and were indexed by PubMed and Web of Science (WoS). Microsoft Excel and bibliometric tools (WoS and VOSviewer) were utilized for quantitative and bibliometric network analysis. The measures were investigated on the total number of publications by year, research categories, source journals, other datasets/databases co-used with MEPS, funding sources, collaboration patterns, and research topics.

Findings

A total of 1,953 eligible publications were included in this study with the numbers growing significantly over time. MEPS data were primarily used in healthcare services, public environmental and occupational health research. The journals that published the most papers using MEPS were all in the healthcare research area. Twenty-four other databases were found to be used along with MEPS. Over 3,200 researchers from 1,074 institutions in 25 countries have contributed to the publications. Research funding was supported from federal, private, local, and international agencies. Three clusters of research topics were identified among 235 key terms extracted from titles and abstracts.

Originality/value

Our results illustrated the broad landscape of the research efforts that MEPS data have supported and substantiated the value of AHRQ's effort of providing MEPS to the public.

Research on social media and journalism (2003-2017): a bibliometric and content review

Abstract This paper introduces a bibliometric review of the scientific literature on social media and journalism published by journals indexed by Journal Citation Reports until 2017 (n=213). Besides descriptive measurements, it provides a co-citation and co-word analysis. A quantitative content analysis complements the bibliometric approach. Thus, the paper offers a conceptual and structural analysis of the field of study. Results show that the number of articles on the topic is growing steadily since 2014. United States, Australia and England stand as the most productive countries. Studies are based mostly on data from Europe and North America. Three conceptual clusters are identified: audience participation, user generated content and the influence of social media on journalistic professional values and practices. Most of the studies did not consider specific services but focused on the general concept of “social media”. Twitter was the most analyzed platform until recent years, when scholarly attention changed towards Facebook. Research has preferred focusing on political information in detriment of other branches of journalism. The most employed methods are content analysis and in-depth interviews. Further use of surveys and social network analysis, as well as stronger focus on visual studies, is suggested.

Application of entity linking to identify research fronts and trends

Studying research fronts enables researchers to understand how their academic fields emerged, how they are currently developing and their changes over time. While topic modelling tools help discover themes in documents, they employ a “bag-of-words” approach and require researchers to manually label categories, specify the number of topics a priori, and make assumptions about word distributions in documents. This paper proposes an alternative approach based on entity linking, which links word strings to entities from a knowledge base, to help solve issues associated with “bag-of-words” approaches by automatically identifying topics based on entity mentions. To study topic trends and popularity, we use four indicators—Mann–Kendall’s test, Sen’s slope analysis, z-score values and Kleinberg’s burst detection algorithm. The combination of these indicators helps us understand which topics are particularly active (“hot” topics), which are decreasing (“cold” topics or past “bursty” topics) and which are maturely developed. We apply the approach and indicators to the fields of Information Science and Accounting.