This article aims to present a bibliometric analysis of Smart Cities. The study analyzes the most important journals during the period between 1991 and 2019. It provides helpful insights into the document types, the distribution of countries/territories, the distribution of institutions, the authors’ geographical distribution, the most active authors and their research interests or fields, the relationships between principal authors and more relevant publications, and the most cited articles. This paper also provides important information about the core and historical references and the most cited papers. The analysis used the keywords and thematic noun-phrases in the titles and abstracts of the sample papers to explore the hot research topics in the top journals (e.g., ‘Smart Cities’, ‘Intelligent Cities’, ‘Sustainable Cities’, ‘e-Government’, ‘Digital Transformation’, ‘Knowledge-Based City’, etc.). The main objective is to have a quantitative description of the published literature about Smart Cities; this description will be the basis for the development of a methodology for the diagnosis of the maturity of a Smart City. The results presented here help to define the scientific concept of Smart Cities and to measure the importance that the term has gained through the years. The study has allowed us to know the main indicators of the published literature in depth, from the date of publication of the first articles and the evolution of these indicators to the present day. From the main indicators in the literature, some were selected to be applied: The most influential journals on Smart Cities according to the general citation structure in Smart Cities, Global Impact Factor of Smart Cities, number of publications, publications on Smart Cities around the world, and their correlation.

This paper presents a quantitative vision of the study of artificial intelligence risk assessment in business based on a bibliometric analysis of the most relevant publications. The main goal is to determine whether the risk assessment of artificial intelligence systems used in businesses is really a subject of increasing interest and to identify the most influential and productive sources of scientific research in this area. Data were collected from the Web of Science Core Collection, one of the most complete and prestigious databases. Regarding the temporal evolution of publications and citations this study evidences, this research subject shows rapid growth in the number of publications (at a compound annual rate of 31.20% from 2018 to 2024 inclusive), showing its high attraction for researchers, responding to the need to implement systematic risk assessment processes in the organizations using AI to mitigate potential harms, ensure compliance with regulations, and enhance artificial intelligence systems’ trust and adoption. Especially after the surge of large language models like ChatGPT or Gemini, AI is revolutionizing the dynamics of human–computer interaction using natural language, video, and audio. However, as the scientific community initiates rigorous studies on AI risk assessment within organizational contexts, it is imperative to consider critical issues such as data privacy, ethics, bias, and hallucinations to ensure the successful integration and interaction of AI systems with human operators. Furthermore, this paper constitutes a starting point, including for any researcher who wants to be introduced to this topic, indicating new challenges that should be dealt by researchers interested in AI and hot topics, in addition to the most relevant literature, authors, and journals about this research subject.

El uso de las redes socials en educación es muy relevante, tanto para educadores como estudiantes, para promover el aprendizaje. Ello ha sido observado por la literatura, la cual observa un importante crecimiento en el número de artículos analizando dicho tema.. Sin embargo este estudio es todavía escaso. El objetivo de este artículo es presentar una revisión bilométrica del uso de las redes sociales en educación, con objeto de identificar el desarrollo del área, y sus tendencias. Para ello, el trabajo utiliza datos de la Web of Science, además de instrumenos bibliométricos y el programa VOS viewer, enfatizando el estudio de la co-ocurrencia de palabra clave. Dado ello, el artículo subraya las tendencias actuales en el area, hecho que puede ayudar a investigadores y profesionales para entender el estado del arte en el área.

En la presente comunicación se expone el resumen de un estudio bibliométrico realizado sobre el uso de Twitter en la docencia, empleando para ello la base de datos de utilizando la base de datos de la Web of Science, identificando los artículos más relevantes clasificada por artículos, autores, y países.-------------------------------------------------------------------In thepresentcommunicationthesummary of a bibliometricstudymadeonthe use of Twitter in teachingisexposed, usingforthisthedatabase of usingtheWeb of Sciencedatabase, identifyingthemostrelevantarticlesclassifiedbyarticles, authors, and countries.

Ciberseguridad y bibliotecas: apuntes para una propuesta de formación sobre riesgo tecnológico en bibliotecas