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      O impacto da pandemia da COVID-19 para a divulgação científica Translated title: Impact of COVID-19 pandemic on science communication

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          The Rise of Altmetrics

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            The Use of Social Media to Increase the Impact of Health Research: Systematic Review

            Background Academics in all disciplines increasingly use social media to share their publications on the internet, reaching out to different audiences. In the last few years, specific indicators of social media impact have been developed (eg, Altmetrics), to complement traditional bibliometric indicators (eg, citation count and h-index). In health research, it is unclear whether social media impact also translates into research impact. Objective The primary aim of this study was to systematically review the literature on the impact of using social media on the dissemination of health research. The secondary aim was to assess the correlation between Altmetrics and traditional citation-based metrics. Methods We conducted a systematic review to identify studies that evaluated the use of social media to disseminate research published in health-related journals. We specifically looked at studies that described experimental or correlational studies linking the use of social media with outcomes related to bibliometrics. We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica dataBASE (EMBASE), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases using a predefined search strategy (International Prospective Register of Systematic Reviews: CRD42017057709). We conducted independent and duplicate study selection and data extraction. Given the heterogeneity of the included studies, we summarized the findings through a narrative synthesis. Results Of a total of 18,624 retrieved citations, we included 51 studies: 7 (14%) impact studies (answering the primary aim) and 44 (86%) correlational studies (answering the secondary aim). Impact studies reported mixed results with several limitations, including the use of interventions of inappropriately low intensity and short duration. The majority of correlational studies suggested a positive association between traditional bibliometrics and social media metrics (eg, number of mentions) in health research. Conclusions We have identified suggestive yet inconclusive evidence on the impact of using social media to increase the number of citations in health research. Further studies with better design are needed to assess the causal link between social media impact and bibliometrics.
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              Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining.

              The COVID-19 pandemic has wreaked havoc in every country in the world, with serious health-related, economic, and social consequences. Since its outbreak in March 2020, many researchers from different fields have joined forces to provide a wide range of solutions, and the support for this work from artificial intelligence (AI) and other emerging concepts linked to intelligent data analysis has been decisive. The enormous amount of research and the high number of publications during this period makes it difficult to obtain an overall view of the different applications of AI to the management of COVID-19 and an understanding of how research in this field has been evolving. Therefore, in this paper, we carry out a scientometric analysis of this area supported by text mining, including a review of 18,955 publications related to AI and COVID-19 from the Scopus database from March 2020 to June 2021 inclusive. For this purpose, we used VOSviewer software, which was developed by researchers at Leiden University in the Netherlands. This allowed us to examine the exponential growth in research on this issue and its distribution by country, and to highlight the clear hegemony of the United States (USA) and China in this respect. We used an automatic process to extract topics of research interest and observed that the most important current lines of research focused on patient-based solutions. We also identified the most relevant journals in terms of the COVID-19 pandemic, demonstrated the growing value of open-access publication, and highlighted the most influential authors by means of an analysis of citations and co-citations. This study provides an overview of the current status of research on the application of AI to the pandemic.
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                Author and article information

                Journal
                codas
                CoDAS
                CoDAS
                Sociedade Brasileira de Fonoaudiologia (São Paulo, SP, Brazil )
                2317-1782
                2024
                : 36
                : 2
                : e20240068
                Affiliations
                [02] Ribeirão Preto orgnameUniversidade de São Paulo orgdiv1Programa de Pós-graduação em Psicobiologia Brazil
                [04] Brasília Distrito Federal orgnameUniversidade de Brasília Brazil
                [03] Belo Horizonte Minas Gerais orgnameUniversidade Federal de Minas Gerais Brazil
                [01] São Paulo São Paulo orgnameFaculdade de Ciências Médicas da Santa Casa de São Paulo Brazil
                [05] João Pessoa orgnameUniversidade Federal da Paraíba Brazil
                Article
                S2317-17822024000200101 S2317-1782(24)03600200101
                10.1590/2317-1782/20242024068pt
                00e2f891-1a6e-4abf-b178-148077efaf5d

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 28 February 2024
                : 28 February 2024
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 24, Pages: 0
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