Corrigendum: Corrigendum: Evaluative altmetrics: is there evidence for its application to research evaluation?

[This corrects the article DOI: 10.3389/frma.2023.1295959.].

Corrigendum: Evaluative altmetrics: is there evidence for its application to research evaluation?

[This corrects the article DOI: 10.3389/frma.2023.1188131.].

Evaluative altmetrics: is there evidence for its application to research evaluation?

Introduction: Altmetrics have been demonstrated as a promising tool for analyzing scientific communication on social media. Nevertheless, its application for research evaluation remains underdeveloped, despite the advancement of research in the study of diverse scientific interactions. Methods: This paper develops a method for applying altmetrics in the evaluation of researchers, focusing on a case study of the Environment/Ecology ESI field publications by researchers at the University of Granada. We considered Twitter as a mirror of social attention, news outlets as media, and Wikipedia as educational, exploring mentions from these three sources and the associated actors in their respective media, contextualizing them using various metrics. Results: Our analysis evaluated different dimensions such as the type of audience, local attention, engagement generated around the mention, and the profile of the actor. Our methodology effectively provided dashboards that gave a comprehensive view of the different instances of social attention at the author level. Discussion: The use of altmetrics for research evaluation presents significant potential, as shown by our case study. While this is a novel method, our results suggest that altmetrics could provide valuable insights into the social attention that researchers garner. This can be an important tool for research evaluation, expanding our understanding beyond traditional metrics.

COVID-19 and the scientific publishing system: growth, open access and scientific fields.

We model the growth of scientific literature related to COVID-19 and forecast the expected growth from 1 June 2021. Considering the significant scientific and financial efforts made by the research community to find solutions to end the COVID-19 pandemic, an unprecedented volume of scientific outputs is being produced. This questions the capacity of scientists, politicians and citizens to maintain infrastructure, digest content and take scientifically informed decisions. A crucial aspect is to make predictions to prepare for such a large corpus of scientific literature. Here we base our predictions on the Autoregressive Integrated Moving Average (ARIMA) and exponential smoothing models using the Dimensions database. This source has the particularity of including in the metadata information on the date in which papers were indexed. We present global predictions, plus predictions in three specific settings: by type of access (Open Access), by domain-specific repository (SSRN and MedRxiv) and by several research fields. We conclude by discussing our findings. Supplementary Information: The online version contains supplementary material available at 10.1007/s11192-022-04536-x.

Identifying and characterizing social media communities: a socio-semantic network approach to altmetrics.

Altmetric indicators allow exploring and profiling individuals who discuss and share scientific literature in social media. But it is still a challenge to identify and characterize communities based on the research topics in which they are interested as social and geographic proximity also influence interactions. This paper proposes a new method which profiles social media users based on their interest on research topics using altmetric data. Social media users are clustered based on the topics related to the research publications they share in social media. This allows removing linkages which respond to social or personal proximity and identifying disconnected users who may have similar research interests. We test this method for users tweeting publications from the fields of Information Science & Library Science, and Microbiology. We conclude by discussing the potential application of this method and how it can assist information professionals, policy managers and academics to understand and identify the main actors discussing research literature in social media.

Bibliometric Reports for Institutions: Best Practices in a Responsible Metrics Scenario.

Carrying out bibliometric reports is one of the common tasks performed by librarians and practitioners within the framework of their professional duties. The emergence of novel data sources, the need to measure new research activities and the growing demand for fairer and more equitable evaluation within the framework of the Responsible Metrics movement has led to calls for a review of the traditional approaches to these types of reports. The main goal of this study is to outline a series of recommendations for bibliometricians, consultants and research support librarians when drafting bibliometric reports in their institutions. These best practices can significantly enhance the quality and utility of bibliometric reports, posing their practitioners as key players in the science management process.

Science through Wikipedia: A novel representation of open knowledge through co-citation networks.

This study provides an overview of science from the Wikipedia perspective. A methodology has been established for the analysis of how Wikipedia editors regard science through their references to scientific papers. The method of co-citation has been adapted to this context in order to generate Pathfinder networks (PFNET) that highlight the most relevant scientific journals and categories, and their interactions in order to find out how scientific literature is consumed through this open encyclopaedia. In addition to this, their obsolescence has been studied through Price index. A total of 1 433 457 references available at Altmetric.com have been initially taken into account. After pre-processing and linking them to the data from Elsevier's CiteScore Metrics the sample was reduced to 847 512 references made by 193 802 Wikipedia articles to 598 746 scientific articles belonging to 14 149 journals indexed in Scopus. As highlighted results we found a significative presence of "Medicine" and "Biochemistry, Genetics and Molecular Biology" papers and that the most important journals are multidisciplinary in nature, suggesting also that high-impact factor journals were more likely to be cited. Furthermore, only 13.44% of Wikipedia citations are to Open Access journals.

Mapping social media attention in Microbiology: identifying main topics and actors.

This paper aims to map and identify topics of interest within the field of Microbiology and identify the main sources driving such attention. We combine data from Web of Science and Altmetric.com, a platform which retrieves mentions to scientific literature from social media and other non-academic communication outlets. We focus on the dissemination of microbial publications in Twitter, news media and policy briefs. A two-mode network of social accounts shows distinctive areas of activity. We identify a cluster of papers mentioned solely by regional news media. A central area of the network is formed by papers discussed by the three outlets. A large portion of the network is driven by Twitter activity. When analyzing top actors contributing to such network, we observe that more than half of the Twitter accounts are bots, mentioning 32% of the documents in our dataset. Within news media outlets, there is a predominance of popular science outlets. With regard to policy briefs, both international and national bodies are represented. Finally, our topic analysis shows that the thematic focus of papers mentioned varies by outlet. While news media cover the wider range of topics, policy briefs are focused on translational medicine and bacterial outbreaks.

Investigación de excelencia en España: ¿protagonistas o papeles secundarios? / Research excellence in Spain: main or secondary roles for researchers?

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