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Though classic servants like the butler or the governess have largely vanished, the Internet is filled with servers: web, ftp, mail, and others perform their daily drudgery, going about their business noiselessly and unnoticed. Why then are current-day digital drudges called servers? Markus Krajewski explores this question by going from the present back to the Baroque to study historical aspects of service through various perspectives, be it the servants' relationship to architecture or their function in literary or scientific contexts. At the intersection of media studies, cultural history, and literature, this work recounts the gradual transition of agency from human to nonhuman actors to show how the concept of the digital server stems from the classic role of the servant.

Purpose The purpose of this study is to assess the coverage of the scientific literature in Scopus and Web of Science from the perspective of research evaluation. Design/methodology/approach The academic communities of Norway have agreed on certain criteria for what should be included as original research publications in research evaluation and funding contexts. These criteria have been applied since 2004 in a comprehensive bibliographic database called the Norwegian Science Index (NSI). The relative coverages of Scopus and Web of Science are compared with regard to publication type, field of research and language. Findings Our results show that Scopus covers 72 percent of the total Norwegian scientific and scholarly publication output in 2015 and 2016, while the corresponding figure for Web of Science Core Collection is 69 percent. The coverages are most comprehensive in medicine and health (89 and 87 percent) and in the natural sciences and technology (85 and 84 percent). The social sciences (48 percent in Scopus and 40 percent in Web of Science Core Collection) and particularly the humanities (27 and 23 percent) are much less covered in the two international data sources. Research limitation Comparing with data from only one country is a limitation of the study, but the criteria used to define a country’s scientific output as well as the identification of patterns of field-dependent partial representations in Scopus and Web of Science should be recognizable and useful also for other countries. Originality/value The novelty of this study is the criteria-based approach to studying coverage problems in the two data sources.

Purpose: The aim of this study is to conduct a comprehensive review of scientific articles concerning artificial intelligence (AI) applications in electronic commerce through bibliometric analysis.   Theoretical Framework: The current study utilized both the SCOPUS and Web of Science (WoS) databases to enrich the analysis with a wider selection of papers in the field, incorporating an examination of the most cited documents.   Design/Methodology/Approach: The dataset for analysis was selected according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, integrating data from Scopus and WoS through R software, specifically using the biblioshiny library. It includes 8372 papers published from 1995 to 2023. This study's data analysis used two approaches: descriptive analysis to examine the data quantitatively and scientific mapping to explore the intellectual and social structures within the dataset.   Findings: The results reveal significant trends in the application of artificial intelligence in e-commerce, highlighting the rapid growth of interest in this area over the last decade. China emerges as the country with the highest number of citations, with ZHANG Y identified as the most relevant author and HU M as the most cited author. Furthermore, the study identifies prevalent keywords used by the authors, including sentiment analysis and recommendation systems.   Research, Practical & Social Implications: This study underscores the transformative potential of AI in enhancing e-commerce practices, offering insights for both academic researchers and industry professionals by providing valuable perspectives on current trends and contributions.   Originality/Value: The value of the study lies in its comprehensive bibliometric approach, which integrates two major databases to explore AI's applications in e-commerce. This deviation from previous reviews, which often rely on a single database, provides a deeper understanding of the current landscape and future directions in this field. Objetivo: O objetivo deste estudo é realizar uma revisão abrangente de artigos científicos sobre as aplicações de inteligência artificial (IA) no comércio eletrônico por meio de análise bibliométrica. Referencial teórico: O estudo atual utilizou tanto as bases de dados SCOPUS quanto Web of Science (WoS) para enriquecer a análise com uma seleção mais ampla de artigos no campo, incorporando um exame dos documentos mais citados. Desenho/metodologia/abordagem: O conjunto de dados para análise foi selecionado de acordo com o framework PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), integrando dados do Scopus e WoS por meio do software R, especificamente utilizando a biblioteca biblioshiny, e inclui 8372 artigos publicados de 1995 a 2023. A análise de dados deste estudo utilizou duas abordagens: análise descritiva para examinar os dados quantitativamente e mapeamento científico para explorar as estruturas intelectuais e sociais dentro do conjunto de dados. Resultados: Os resultados revelam tendências significativas na aplicação da inteligência artificial no comércio eletrônico, destacando o rápido crescimento do interesse nesta área ao longo da última década. A China emerge como o país com o maior número de citações, com ZHANG Y identificado como o autor mais relevante e HU M como o autor mais citado. Além disso, o estudo identifica palavras-chave prevalentes usadas pelos autores, incluindo análise de sentimento e sistemas de recomendação. Pesquisa, implicações práticas e sociais: Este estudo destaca o potencial transformador da IA em aprimorar práticas de comércio eletrônico, oferecendo insights tanto para pesquisadores acadêmicos quanto profissionais da indústria, fornecendo perspectivas valiosas sobre tendências atuais e contribuições. Originalidade/valor: O valor do estudo reside em sua abordagem bibliométrica abrangente, que integra duas bases de dados principais para explorar as aplicações da IA no comércio eletrônico. Esta divergência das revisões anteriores, que frequentemente se baseiam em uma única base de dados, proporciona uma compreensão mais profunda do cenário atual e das direções futuras neste campo. Propósito: El objetivo de este estudio es realizar una revisión exhaustiva de artículos científicos sobre las aplicaciones de la inteligencia artificial (IA) en el comercio electrónico a través de análisis bibliométrico. Marco  teórico: El estudio actual utilizó tanto las bases de datos SCOPUS como Web of Science (WoS) para enriquecer el análisis con una selección más amplia de artículos en el campo, incorporando un examen de los documentos más citados. Metodología: El conjunto de datos para el análisis fue seleccionado de acuerdo con el marco PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), integrando datos de Scopus y WoS a través del software R, específicamente utilizando la biblioteca biblioshiny, e incluye 8372 artículos publicados desde 1995 hasta 2023. El análisis de datos de este estudio utilizó dos enfoques: análisis descriptivo para examinar los datos cuantitativamente y mapeo científico para explorar las estructuras intelectuales y sociales dentro del conjunto de datos. Conclusiones: Los resultados revelan tendencias significativas en la aplicación de la inteligencia artificial en el comercio electrónico, destacando el rápido crecimiento del interés en esta área durante la última década. China emerge como el país con el mayor número de citas, con ZHANG Y identificado como el autor más relevante y HU M como el autor más citado. Además, el estudio identifica palabras clave prevalentes utilizadas por los autores, incluyendo análisis de sentimientos y sistemas de recomendación. Implicaciones de la Investigación: Este estudio subraya el potencial transformador de la IA en mejorar las prácticas de comercio electrónico, ofreciendo ideas tanto para investigadores académicos como profesionales de la industria, proporcionando perspectivas valiosas sobre tendencias actuales y contribuciones. Originalidad/valor: El valor del estudio radica en su enfoque bibliométrico exhaustivo, que integra dos bases de datos principales para explorar las aplicaciones de la IA en el comercio electrónico. Esta desviación de revisiones anteriores, que a menudo se basan en una sola base de datos, proporciona una comprensión más profunda del panorama actual y las direcciones futuras en este campo.

Alzheimer's disease is the most common cause of dementia. It is an increasingly serious global health problem and has a significant impact on individuals and society. However, the precise cause of Alzheimer's disease is still unknown. In this study, 11,748 Web-of-Science-indexed manuscripts regarding Alzheimer's disease, all published from 2015 to 2019, and their 693,938 references were analyzed. A document co-citation network map was drawn using CiteSpace software. Research frontiers and development trends were determined by retrieving subject headings with apparent changing word frequency trends, which can be used to forecast future research developments in Alzheimer's disease.

The current study aimed to provide a comprehensive bibliometric overview of the literature on curcumin, complementing the previous reviews and meta-analyses on its potential health benefits. Bibliometric data for the current analysis were extracted from the Web of Science Core Collection database, using the search string TOPIC=(“curcumin*”), and analyzed by the VOSviewer software. The search yielded 18,036 manuscripts. The ratio of original articles to reviews was 10.4:1. More than half of the papers have been published since 2014. The major contributing countries were the United States, China, India, Japan, and South Korea. These publications were mainly published in journals representing the following scientific disciplines: biochemistry, chemistry, oncology, and pharmacology. There was a significant positive correlation between the total publication count and averaged citations per manuscript for affiliations, but not for countries/regions and journals. Chemicals that were frequently mentioned in the keywords of evaluated curcumin publications included curcuminoids, resveratrol, chitosan, flavonoids, quercetin, and polyphenols. The literature mainly focused on curcumin’s effects against cancer, inflammation, and oxidative stress. Cancer types most frequently investigated were breast, colon, colorectal, pancreatic, and prostate cancers.

Objective: This study aimed to evaluate the current research hotspots and development tendency of Transcranial Direct Current Stimulation(tDCS) in the field of neurobiology from a bibliometric perspective by providing visualized information to scientists and clinicians. Methods: Publications related to tDCS published between 2000 and 2022 were retrieved from the Web of Science Core Collection (WOSCC) on May 5, 2022. Bibliometric features including the number of publications and citations, citation frequency, H-index, journal’s impact factors and journal citation reports were summarized using Microsoft Office Excel. Co-authorship, citation, co-citation, and co-occurrence analyses between countries, institutions, journals, authors, references and keywords were analyzed and visualized using CiteSpace (version 6.1.R3). Results: A total of 4756 publications on tDCS fulfilled the criteria we selected and then were extracted from the WoS. The United States (1190 publications, 25.02%) and Harvard University (185 publications, 3.89%) were the leading contributors among all the countries and institutions, respectively. Nitsche MA and Fregni F, the key researchers, made great achievements in tDCS. Brain Stimulation (306 publications) had the highest number of publications relevant to tDCS, and the highest citations (4,042 times). In terms of potential hotspots, we learn through reference co-citation analysis timeline viewer related to tDCS that “depression”#0, “Sensorimotor network”#10, “working memory”#11, “Transcranial magnetic stimulation”#9 might be the future research hotspots, while keywords with the strong burst and still ongoing were “intensity”(2018-2022), “impairment”(2020-2022), “efficacy”(2020-2022) and “guideline”(2020-2022). Conclusions: This was the first-ever study of peer-reviewed publications relative to tDCS using several scientometric and visual analytic methods to quantitatively and qualitatively reveal the current research status and trends in the field of tDCS. Through the bibliometric method, we gained an in-depth understanding of the current research status and development trend on tDCS. Our research and analysis results may provide some practical sources for academic scholars and clinicians.

The use of metrics in the evaluation of a researcher’s output is now a common practice and has a decisive influence on their career (metricracy). It is widespread to consider the Journal Impact Factor (JIF) as a means of assessing the quality and significance of a paper. It has been discussed that it is appropriate to use a metric that evaluates each paper based on its citations rather than the journal in which it was published. Other parameters such as the number of years since publication, the number of authors and their position in the author list are also discussed and a formula for scoring each published article is proposed.

Web of Science (WoS) is the world’s oldest, most widely used and authoritative database of research publications and citations. Based on the Science Citation Index, founded by Eugene Garfield in 1964, it has expanded its selective, balanced, and complete coverage of the world’s leading research to cover around 34,000 journals today. A wide range of use cases are supported by WoS from daily search and discovery by researchers worldwide through to the supply of analytical data sets and the provision of specialized access to raw data for bibliometric partners. A long- and well-established network of such partners enables the Institute for Scientific Information (ISI) to continue to work closely with bibliometric groups around the world to the benefit of both the community and the services that the company provides to researchers and analysts.

Scientists are increasingly overwhelmed by the volume of articles being published. The total number of articles indexed in Scopus and Web of Science has grown exponentially in recent years; in 2022 the article total was ∼47% higher than in 2016, which has outpaced the limited growth—if any—in the number of practicing scientists. Thus, publication workload per scientist has increased dramatically. We define this problem as “the strain on scientific publishing.” To analyze this strain, we present five data-driven metrics showing publisher growth, processing times, and citation behaviors. We draw these data from web scrapes, and from publishers through their websites or upon request. Specific groups have disproportionately grown in their articles published per year, contributing to this strain. Some publishers enabled this growth by hosting “special issues” with reduced turnaround times. Given pressures on researchers to “publish or perish” to compete for funding, this strain was likely amplified by these offers to publish more articles. We also observed widespread year-over-year inflation of journal impact factors coinciding with this strain, which risks confusing quality signals. Such exponential growth cannot be sustained. The metrics we define here should enable this evolving conversation to reach actionable solutions to address the strain on scientific publishing.