COVID-19 has changed our lives forever. The world we knew until now has been transformed and nowadays we live in a completely new scenario in a perpetual restructuring transition, in which the way we live, relate, and communicate with others has been altered permanently. Within this context, risk communication is playing a decisive role when informing, transmitting, and channeling the flow of information in society. COVID-19 has posed a real pandemic risk management challenge in terms of impact, preparedness, response, and mitigation by governments, health organizations, non-governmental organizations (NGOs), mass media, and stakeholders. In this study, we monitored the digital ecosystems during March and April 2020, and we obtained a sample of 106,261 communications through the analysis of APIs and Web Scraping techniques. This study examines how social media has affected risk communication in uncertain contexts and its impact on the emotions and sentiments derived from the semantic analysis in Spanish society during the COVID-19 pandemic.

In the last decade, the advertising industry has experienced a quantum leap, powered by recent advances in neuroscience, a large investment in artificial intelligence, and a high degree of consumer expertise. Within this context, opinion mining, sentiment analysis, and emotion understanding bring us closer to one of the most sought-after objectives of advertising: to offer relevant ads at scale. The importance of studies about opinion mining, sentiment analysis, and emotion understanding in advertising has been rising exponentially over the last years. The peak of this new situation has been the interest of the research community in studying the relationship between such innovations and the spread of smart and contextual advertising. This article analyzes those works that address the relationship between sentiment analysis, opinion mining, and emotion understanding in advertising. The main objective is to clarify the current state of these studies, explore issues, methods, findings, themes, and gaps as well as to define their significance within the current convergence advertising research scenario. To reach such objectives, a bibliometric analysis was conducted, retrieving and analyzing 919 research works published between 2010 and 2019 based on results from Web of Science (WoS).

Opinion mining and sentiment analysis has become ubiquitous in our society, with applications in online searching, computer vision, image understanding, artificial intelligence and marketing communications (MarCom). Within this context, opinion mining and sentiment analysis in marketing communications (OMSAMC) has a strong role in the development of the field by allowing us to understand whether people are satisfied or dissatisfied with our service or product in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To the best of our knowledge, there is no science mapping analysis covering the research about opinion mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work during the last two decades in this interdisciplinary area and to show trends that could be the basis for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer and InCites based on results from Web of Science (WoS). The results of this analysis show the evolution of the field, by highlighting the most notable authors, institutions, keywords, publications, countries, categories and journals.

Mass cytometry (CyTOF) is a relatively novel technique for the multiparametric analysis of single-cell features with an increasing central role in cell biology, immunology, pharmacology, and biomedicine. This technique mixes the fundamentals of flow cytometry with mass spectrometry and is mainly used for in-depth studies of the immune system and diseases with a significant immune load, such as cancer, autoimmune diseases, and viral diseases like HIV or the recently emerged COVID-19, produced by the SARS-CoV-2 coronavirus. The objective of this study was to provide a useful insight into the evolution of the mass cytometry research field, revealing the knowledge structure (conceptual and social) and authors, countries, sources, documents, and organizations that have made the most significant contribution to its development. We retrieved 937 articles from the Web of Science (2010–2019), analysed 71 Highly Cited Papers (HCP) through the H-Classics methodology and computed the data by using Bibliometrix R package. HCP sources corresponded to high-impact journals, such as Nature Biotechnology and Cell, and its production was concentrated in the US, and specifically Stanford University, affiliation of the most relevant authors in the field. HCPs analysis confirmed great interest in the study of the immune system and complex data processing in the mass cytometry research field.

Blockchain is a technology that will change the relationships between the different actors in society, individuals, companies and administration, in aspects as important as taxation, by implementing concepts such as Self-sovereign identity (SSI) and Smart Contracts; which support, for example, virtual currencies, that are not controlled by any state, financial institution or centralized company. Hence, the growing interest of researchers, investors, traders, marketers, enterprises, and administrations to know the scope of this new technology and its tax implications. The main objective of this work is to clarify the status of these studies, explore issues, methods, findings, and trends as well as to define their meaning within the current research scenario. To achieve these objectives, bibliometric analysis was carried out, retrieving 349 research papers, and analyzing 343 papers published between 2015–2019 based on the results of the Web of Science (WoS).

Neuromarketing, consumer neuroscience and neuroaesthetics are a broad research area of neuroscience with an extensive background in scientific publications. Thus, the present study aims to identify the highly cited papers (HCPs) in this research field, to deliver a summary of the academic work produced during the last decade in this area, and to show patterns, features, and trends that define the past, present, and future of this specific area of knowledge. The HCPs show a perspective of those documents that, historically, have attracted great interest from a research community and that could be considered as the basis of the research field. In this study, we retrieved 907 documents and analyzed, through H-Classics methodology, 50 HCPs identified in the Web of Science (WoS) during the period 2010–2019. The H-Classic approach offers an objective method to identify core knowledge in neuroscience disciplines such as neuromarketing, consumer neuroscience, and neuroaesthetics. To accomplish this study, we used Bibliometrix R Package and SciMAT software. This analysis provides results that give us a useful insight into the development of this field of research, revealing those scientific actors who have made the greatest contribution to its development: authors, institutions, sources, countries as well as documents and references.

Innovations in dental sciences are potentially disruptive; however, the language barrier in the case of Latin America and the Caribbean (LAC) limits access to scientific studies. There is a necessity to measure the development of dental research across the LAC region, where economic power and postgraduate education access vary significantly. This article aims to analyze documents, citations, and journals and compare the SJR, H-Index, citation rates, and Co-occurrence Networks (Keywords) between dental journals published in LAC and the rest of the world, according to the report of Scimago Journal and Country Rank, between the years 1996 and 2020. Results show that Brazil leads dental research in the LAC, scoring the highest number of published documents, citations, and SJR metrics. The mean H-index and SJR of LAC dentistry journals are significantly lower than those of other regions (p < 0.03); however, there are no significant differences in the mean total citations in the last 3 years between LAC and other regions (p > 0.15). This suggests that the articles published in dentistry journals from LAC are being cited in similar proportions to the journals of other regions, but a large portion of these citations came from publications with low scientific impact.

Open Science (OS) has been rapidly evolving in recent years, but there is still work to be done to return Science to researchers and citizens who pay for it. Technological advancements have enabled Open Science to transform the way scientific research is conducted, facilitating collaboration and innovation among researchers. As a result, OS is expected to play an increasingly important role in scientific research and innovation in the years to come, driving discoveries and advancements in various fields. However, OS also poses challenges, including the potential for bias and discrimination in research. This chapter explores the challenges that need to be addressed to fully implement OS globally, outlining the barriers that need to be overcome and describing the complexity of the changes that come with this new research approach. Additionally, the chapter discusses the impact of Artificial Intelligence on addressing these challenges, while also creating new ones.