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The main objective of this work is to determine the collaboration level of Latin American universities with companies in terms of scientific co-authorship, and to identify the main institutions involved in these collaborations. To do this, all publications from 2009 to 2018 with at least one co-author belonging to each of 20 Latin American countries, and another co-author affiliated to a company, were extracted from Elsevier’s Scival (powered by Scopus data), obtaining a set of 22,469 records, from which 1,531 companies (both of public and private nature) and 428 Latin American universities were identified. Despite publications co-authored by universities and companies are highly-cited, results evidence low percentages of academic collaboration between Latin American universities and companies over the period. Just few firms (mainly from Pharmacy, Technology and Petroleum markets) have established strong connections with few universities, mainly from Brazil, whose performance masks the remaining minor linkages established in other countries. Otherwise, the presence of publicly-traded companies (e.g., Petrobras, Agrosavia, Embrapa, YPF or Petróleos Mexicanos) is also remarkable. The establishment of stable public policies aimed at promoting and strengthening University-Industry relations in the region, and based on the integration and regulation of these actions in the researcher's activities, is recommended.

The interconnection between the Dimensions database and Altmetric.com; provides an opportunity to carry out a worldwide analysis on altmetrics coverage of scientific literature, analyzing the percentage of documents with altmetric mentions not only in general (indexed documents), but also filtered according to different units of analysis. In order to do so, the Dimensions Pro version database was directly used to retrieve 97,531,400 documents, which were subsequently filtered to obtain the top journals, countries, cities, institutions, research fields and funding bodies according to the total number of publications indexed in the database. For each entity and year of publication (from 2000 to 2017), the corresponding percentage of publications cited and the Altmetric Attention Score (% mentioned) were calculated. The main results indicate that the total number of publications with an Altmetric Attention Score (AAS) of one or over one is low (9.4% out of the total coverage), which has been highly concentrated in recent years, and higher for open access documents (18.9%), showing an open access altmetric advantage. Otherwise, English-speaking universities stand out, which determines an increase in the presence of specific cities from Anglo-Saxon countries, diminishing the presence in Japan, China, Russia or India, despite their elevated productivity. Multidisciplinary and medicine-related journals are also highlighted, which in turn influences the research disciplines with a higher AAS (% mentioned): Genetics, Immunology, Microbiology or Medical Microbiology. However, since the conducted analysis has brought out some inconsistencies in the quality of the data, results must be taken with caution.

• DORA and CoARA are redefining academic evaluation standards. • Europe is adopting narrative scientific assessment methods. • Narrative CVs have originated a new field of evaluation. • Narrative Bibliometrics is a new discipline for mapping scientific evidence through data. • Narrative Bibliometrics is a research method adaptable and scalable to any evaluation. The document 'Foundations of Narrative Bibliometrics' provides an analysis of the evolution of scientific assessment, highlighting the influence of manifestos such as DORA and CoARA in shaping ethical and responsible practices in academia, as well as their assimilation by Spanish scientific policies. It connects this context with the contributions of evaluative bibliometrics, emphasising the transition towards a more integrative approach that advocates for a balance between quantitative and qualitative methods in research evaluation. Furthermore, it underscores how the Narrative Curriculum has emerged as one of the fundamental tools in new evaluation processes, as it allows for the description of the complexity and context of academic achievements. Narrative Bibliometrics is proposed, defined as the use of bibliometric indicators to generate stories that support the defence and exposition of a scientific curriculum and/or its individual contributions within the framework of a scientific evaluation process, which demands narratives. To introduce the reader, it presents, in a non-exhaustive manner, sources, indicators, and practical cases for effectively applying Narrative Bibliometrics in various scientific evaluation contexts. Hence, this document contributes to the responsible use of bibliometric indicators, serving as a tool for evaluators and researchers. [ABSTRACT FROM AUTHOR]

Highlights • Google Scholar found nearly all citations found by WoS (95%) and Scopus (92%), and a large amount of unique citations. • About half of Google Scholar unique citations are not from journals. A significant minority (19–38%) are not in English. • Google Scholar unique citations have, on average, a much lower scientific impact than citations also found by WoS/Scopus. • Spearman correlations of citation counts between Google Scholar and WoS/Scopus are strong across all subjects (0.78–0.99). Abstract Despite citation counts from Google Scholar (GS), Web of Science (WoS), and Scopus being widely consulted by researchers and sometimes used in research evaluations, there is no recent or systematic evidence about the differences between them. In response, this paper investigates 2,448,055 citations to 2299 English-language highly-cited documents from 252 GS subject categories published in 2006, comparing GS, the WoS Core Collection, and Scopus. GS consistently found the largest percentage of citations across all areas (93%–96%), far ahead of Scopus (35%–77%) and WoS (27%–73%). GS found nearly all the WoS (95%) and Scopus (92%) citations. Most citations found only by GS were from non-journal sources (48%–65%), including theses, books, conference papers, and unpublished materials. Many were non-English (19%–38%), and they tended to be much less cited than citing sources that were also in Scopus or WoS. Despite the many unique GS citing sources, Spearman correlations between citation counts in GS and WoS or Scopus are high (0.78-0.99). They are lower in the Humanities, and lower between GS and WoS than between GS and Scopus. The results suggest that in all areas GS citation data is essentially a superset of WoS and Scopus, with substantial extra coverage. [ABSTRACT FROM AUTHOR]

The new web-based academic communication platforms do not only enable researchers to better advertise their academic outputs, making them more visible than ever before, but they also provide a wide supply of metrics to help authors better understand the impact their work is making. This study has three objectives: a) to analyse the uptake of some of the most popular platforms (Google Scholar Citations, ResearcherID, ResearchGate, Mendeley and Twitter) by a specific scientific community (bibliometrics, scientometrics, informetrics, webometrics, and altmetrics); b) to compare the metrics available from each platform; and c) to determine the meaning of all these new metrics. To do this, the data available in these platforms about a sample of 811 authors (researchers in bibliometrics for whom a public profile Google Scholar Citations was found) were extracted. A total of 31 metrics were analysed. The results show that a high number of the analysed researchers only had a profile in Google Scholar Citations (159), or only in Google Scholar Citations and ResearchGate (142). Lastly, we find two kinds of metrics of online impact. First, metrics related to connectivity (followers), and second, all metrics associated to academic impact. This second group can further be divided into usage metrics (reads, views), and citation metrics. The results suggest that Google Scholar Citations is the source that provides more comprehensive citation-related data, whereas Twitter stands out in connectivity-related metrics. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to empirically test whether the identification of highly-cited documents through Google Scholar is feasible and reliable. To this end, we carried out a longitudinal analysis (1950–2013), running a generic query (filtered only by year of publication) to minimise the effects of academic search engine optimisation. This gave us a final sample of 64,000 documents (1000 per year). The strong correlation between a document’s citations and its position in the search results (r = −0.67) led us to conclude that Google Scholar is able to identify highly-cited papers effectively. This, combined with Google Scholar’s unique coverage (no restrictions on document type and source), makes the academic search engine an invaluable tool for bibliometric research relating to the identification of the most influential scientific documents. We find evidence, however, that Google Scholar ranks those documents whose language (or geographical web domain) matches with the user’s interface language higher than could be expected based on citations. Nonetheless, this language effect and other factors related to the Google Scholar’s operation, i.e. the proper identification of versions and the date of publication, only have an incidental impact. They do not compromise the ability of Google Scholar to identify the highly-cited papers. [ABSTRACT FROM AUTHOR]

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