Co-word analysis and thematic landscapes in Spanish information science literature, 1985–2014

Why do papers from international collaborations get more citations? A bibliometric analysis of Library and Information Science papers

Scientific activity has become increasingly complex in recent years. The need for international research collaboration has thus become a common pattern in science. In this current landscape, countries face the problem of maintaining their competitiveness while cooperating with other countries to achieve relevant research outputs. In this international context, publications from international collaborations tend to achieve greater scientific impact than those from domestic ones. To design policies that improve the competitiveness of countries and organizations, it thus becomes necessary to understand the factors and mechanisms that influence the benefits and impact of international research. In this regard, the aim of this study is to confirm whether the differences in impact between international and domestic collaborations are affected by their topics and structure. To perform this study, we examined the Library and Information Science category of the Web of Science database between 2015 and 2019. A science mapping analysis approach was used to extract the themes and their structure according to collaboration type and in the whole category (2015–2019). We also looked for differences in these thematic aspects in top countries and in communities of collaborating countries. The results showed that the thematic factor influences the impact of international research, as the themes in this type of collaboration lie at the forefront of the Library and Information Science category (e.g., technologies such as artificial intelligence and social media are found in the category), while domestic collaborations have focused on more well-consolidated themes (e.g., academic libraries and bibliometrics). Organizations, countries, and communities of countries must therefore consider this thematic factor when designing strategies to improve their competitiveness and collaborate.

Presence of women on the editorial boards of the language and linguistics journals in Spain

Many international studies have pointed out the under-representation of women on Editorial Boards of both Science and Social Science journals. Their presence as Editorial Board members is relevant as they influence and reflect the policies of the journal itself. This study analyses the participation of women on the Editorial Boards of the Spanish Language and Linguistics journals in SCOPUS. To this end, 54 journals indexed in SCOPUS were analysed, thus discriminating the gender of all members and the role that each member plays on the Editorial Board. The results show no significant differences in the participation of men and women in these Editorial Boards. It was not found any evidence of gender bias in these journals.

A bibliometrics study of library and information science doctoral dissertations in China from 2011 to 2020

By reading the titles, abstracts, and keywords of LIS doctoral dissertations in China from 2011–2020 and conducting cluster analysis and network analysis of keywords, this study aims to understand the intelligence structure of LIS doctoral dissertations in China, as well as the disciplines and topics intersecting with LIS. The results indicated that Wuhan University had the highest number of doctoral dissertations among all the selected universities offering LIS doctoral education. Research fields mainly focus on online information behavior and information services. The findings could be because of the development of computer science and information technology in the past decade, which indicates that the research direction of LIS in China follows the trend of time development.

Intellectual structure of information science 2011–2020: an author co-citation analysis

Purpose

This study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011–2020. It also examines changes in this structure from 2006–2010 through 2011–2015 to 2016–2020. Results will contribute to a better understanding of the information science research field.

Design/methodology/approach

The well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011–2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor.

Findings

The two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011–2015 but shared dominance with information behavior during 2016–2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016–2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011–2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016–2020.

Originality/value

Author co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.

Mapping the intellectual structure of the coronavirus field (2000-2020): a co-word analysis

Over the two last decades, coronaviruses have affected human life in different ways, especially in terms of health and economy. Due to the profound effects of novel coronaviruses, growing tides of research are emerging in various research fields. This paper employs a co-word analysis approach to map the intellectual structure of the coronavirus literature for a better understanding of how coronavirus research and the disease itself have developed during the target timeframe. A strategic diagram has been drawn to depict the coronavirus domain's structure and development. A detailed picture of coronavirus literature has been extracted from a huge number of papers to provide a quick overview of the coronavirus literature. The main themes of past coronavirus-related publications are (a) "Antibody-Virus Interactions," (b) "Emerging Infectious Diseases," (c) "Protein Structure-based Drug Design and Antiviral Drug Discovery," (d) "Coronavirus Detection Methods," (e) "Viral Pathogenesis and Immunity," and (f) "Animal Coronaviruses." The emerging infectious diseases are mostly related to fatal diseases (such as Middle East respiratory syndrome, severe acute respiratory syndrome, and COVID-19) and animal coronaviruses (including porcine, turkey, feline, canine, equine, and bovine coronaviruses and infectious bronchitis virus), which are capable of placing animal-dependent industries such as the swine and poultry industries under strong economic pressure. Although considerable research into coronavirus has been done, this unique field has not yet matured sufficiently. Therefore, "Antibody-virus Interactions," "Emerging Infectious Diseases," and "Coronavirus Detection Methods" hold interesting, promising research gaps to be both explored and filled in the future.

The Application of Genetic Algorithm in Land Use Optimization Research: A Review

Land use optimization (LUO) first considers which types of land use should exist in a certain area, and secondly, how to allocate these land use types to specific land grid units. As an intelligent global optimization search algorithm, the Genetic Algorithm (GA) has been widely used in this field. However, there are no comprehensive reviews concerning the development process for the application of the Genetic Algorithm in land use optimization (GA-LUO). This article used a bibliometric analysis method to explore current state and development trends for GA-LUO from 1154 relevant documents published over the past 25 years from Web of Science. We also displayed a visualization network from the aspects of core authors, research institutions, and highly cited literature. The results show the following: (1) The countries that published the most articles are the United States and China, and the Chinese Academy of Sciences is the research institution that publishes the most articles. (2) The top 10 cited articles focused on describing how to build GA models for multi-objective LUO. (3) According to the number of keywords that appear for the first time in each time period, we divided the process of GA-LUO into four stages: the presentation and improvement of methods stage (1995–2004), the optimization stage (2005–2008), the hybrid application of multiple models stage (2009–2016), and the introduction of the latest method stage (after 2017). Furthermore, future research trends are mainly manifested in integrating together algorithms with GA and deepening existing research results. This review could help researchers know this research domain well and provide effective solutions for land use problems to ensure the sustainable use of land resources.

Mapping the intellectual structure of GIS-T field (2008–2019): a dynamic co-word analysis

Using geographic information systems (GIS) widely for dealing with transportation problems (is well-known as GIS-T), has made it nessasary for researchers to discover the current state-of-the-art and predict the trends of future research. This paper aims to contribute to a better understanding of GIS-T research area from a longitudinal perspective, over the period 2008–2019. A co-word analysis was used to illustrate all the underlying subfields of GIS-T based on published papers in the Web of Science (WoS) database service. The main knowledge areas representing the intellectual structure of GIS-T including (a) sustainability, (b) health, (c) planning and management, and (d) methods and tools, were detected. Finally, in order to illustrate the structure and development of the identified clusters, two-dimensional maps and strategic diagrams for each period were drawn. This study is the first attempt to employ a text mining method so as to detect the conceptual structure of GIS-T research area from a complex and interdisciplinary literature.

The Methodological Basis of Defining Research Trends and Fronts

The methodological and technical aspects of identifying research fronts and trends in the development of science are considered. Based on the literature data, a comparison of scientometric methods for finding research fronts was carried out: analysis of publication activity, direct citation analysis, co-citation analysis, bibliographic coupling, and content analysis. The advantages of the combined application of various approaches are shown, the role of expert assessment and verification of the results of scientometric analysis is emphasized. We revealed topical problems associated with the detection of scientific fronts by scientometric methods and showed promising directions in their solution.

Mapping the knowledge of green consumption: a meta-analysis

Green consumption can facilitate sustainable industrial development and improve the overall efficiency of resource utilization. In response to rapid economic development and increasing environmental emissions, it is critical to promote green consumption so that the whole society can move toward sustainable development. This study aims to systematically review studies on green consumption by means of meta-analysis, bibliometric analysis, and social network analysis. The results show that green consumption is an interdisciplinary research field, involving environmental science, social science, medical science, economics, and other disciplines. Most productive countries, institutions, authors are identified so that the new researchers in this field can find their research partners. Keywords analysis results help identify the research hotpots in this field. It is suggested that future green consumption research should focus on behavior mechanism, stakeholder coordination, and policy evaluation. In general, the results obtained from this study provide valuable information for researchers and practitioners to promote green consumption research.

Análisis bibliométrico de la Revista Española de Documentación Científica desde su inclusión en la Web of Science (2008-2018)

En este trabajo se presenta un análisis bibliométrico del contenido científico de la Revista Española de Documentación Científica durante el periodo 2008-2018, usando como metodología el análisis de rendimiento y los mapas de la ciencia. En los resultados se muestran, por un lado, algunos de los indicadores bibliométricos de rendimiento básicos, como son: número de documentos publicados, citas obtenidas, evolución del Factor de Impacto, Índice-h, así como los autores más productivos y más citados y la distribución geográfica de las publicaciones. Por otro lado, este análisis muestra la evolución conceptual de la revista basada en los mapas de la ciencia. En la discusión se comparan estos resultados con otros estudios anteriores, que existen sobre la revista, de evolución temática, y sobre la documentación a nivel nacional e internacional. Se concluye indicando cuales son los autores, países y las dos grandes áreas temáticas que destacan en esta revista: bibliometría y web.

Twenty-six years of LIS research focus and hot spots, 1990–2016: A co-word analysis

The purpose of this research is to map and analyse the conceptual and thematic structure of library and information science (LIS) research from the perspective of the co-word analysis. The bibliographical records consist of all the research papers published in the LIS core journals between 1990 and 2016 and indexed in Web of Science. ‘CiteSpace’ was used to visualise the co-word network of LIS studies. The frequency of co-occurrence and centrality scores in the overall structure of the field showed that the word ‘Science’ is the most significant and pivotal keyword among the nodes in the co-word network of LIS literature, and in this respect, the word ‘Library’ is in the second place. However, the results of the social network analysis uncovered that in spite of the high frequency of the word ‘library’, the pivotal role of the term has been exposed to decline over the time. The results of the analysis of co-word clusters showed that ‘information seeking and retrieval’ is the most important research focus in the intellectual structure of LIS literature during 1990–2016. Also, analysis of the hot spots of the LIS research based on Kleinberg algorithm indicated that the words ‘Internet’ and ‘World Wide Web’ have attracted the most attention by LIS scholars during the years under study.

Enriqueciendo la investigación en humanidades digitales. Análisis de textos de claustros académicos de la Universidad de Valencia (1775-1779) con KH Coder

La aplicación de métodos automatizados en cualquier investigación ha facilitado el trasvase de metodologías de una disciplina a otra, permitiendo realizar análisis cuantitativos a textos con estructura o semiestructurados. El objeto de este trabajo es aplicar a un dataset en lenguaje natural -castellano del siglo XVIII- métodos de análisis de la disciplina de documentación. Pretende establecer una metodología automática de análisis cuantitativo y cualitativo de textos, que permita enriquecer en el futuro las conclusiones procedentes del análisis histórico tradicional. Este estudio construye los procedimientos necesarios para poder aplicar análisis de frecuencia, extracción y clasificación de palabras y la construcción de clústeres y redes neuronales con un dataset preexistente, de características muy singulares. Permite validar diferentes utilidades de herramientas y automatizar parte del trabajo de los historiadores, para la edición de los corpus documentales de los claustros universitarios.

National and international trends in library and information science research: A comparative review of the literature

The study is an attempt to understand the trends in LIS research by analyzing published literature on the topic. The study identifies and analyses 39 research papers on LIS research trends in various countries, three papers on LIS research trends in regional countries and 13 papers on LIS research trends with an international perspective. The findings of the study reveal that there is a similarity among various countries as far as the LIS research topics are concerned but with a different focus at different periods. While understanding international research trends in LIS, it was interesting to note that the research trend in China was similar to the worldwide research trend while the pattern in other countries differed.

Análisis de co-palabras aplicado a los artículos muy citados en Biblioteconomía y Ciencias de la Información (2007-2017)

Resumen Se identifican las relaciones entre los conceptos y las áreas temáticas principales dentro de la categoría Biblioteconomía y Ciencias de la Información de Web of Science, en el periodo 2007-2017, utilizando la herramienta analítica “Essential Science Indicators”. Partiendo de los artículos altamente citados, la metodología consistió en la aplicación de análisis de co-palabras así como técnicas estadísticas de análisis multivariante y visualización a través de un mapa de la ciencia. Los resultados principales mostraron que las áreas de mayor interés para los investigadores fueron los estudios sobre la Web 2.0 basados en la participación colaborativa de los usuarios, la evaluación de las actividades científica, las métricas alternativas, o Altmetrics, desarrolladas en las plataformas sociales y académicas, la seguridad y confianza en los entornos virtuales y, por último, la aplicación de plataformas digitales en el comercio electrónico.

Visualising and mapping the intellectual structure of medical big data

In this study, we sought to apply recent advances in informetrics to the analysis of literature related to big data in the field of medicine. Our aim was to elucidate research trends, identify knowledge clusters and decipher the links between them. We also sought to ascertain the theories most commonly applied in the processing of medical data and identify potential research gaps. The most important keywords over the last 10 years have been ‘big data’, ‘data mining’, ‘healthcare’, ‘cloud computing’, ‘machine learning’ and ‘electronic health record system’. These could be viewed as the core issues of research associated with big data in the field of medicine. We also identified a number of keywords that are expected to play a pivotal role in this field in the near future. These terms include the ‘internet of things’, ‘e-health’, ‘sensors’, ‘predictive modeling’, ‘quantified self’, ‘smart city’, ‘wearable device’ and ‘m-health’. Finally, we compiled co-word networks indicating the degree of connectivity between keywords, for use in locating knowledge gaps by revealing the overall context of issues commonly encountered when investigating big data. Our findings form a solid academic foundation on which to develop medical technologies, managerial strategies and theory related to big data.