Comparison of attention for malnutrition research on social media versus academia: Altmetric score analysis

Suzan, Veysel; Ünal, Damla

doi:10.1016/j.nut.2020.111060

Cited by 8 publications

(4 citation statements)

References 23 publications

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“…Although these results show that more attention has been placed on maternal and child malnutrition-related issues, it also suggests that these groups are the most susceptible to malnutrition globally. This assertion is consistent with the micro bibliometric study of health and medical research in Nepal [42] that found child and maternal malnutrition as leading health research and bibliometric evidence comparing malnutrition research in academia against social media [43].…”

Section: Discussionsupporting

confidence: 86%

Malnutrition Research Output: A Bibliometric Analysis for articles Index in Web of Science between 1900 and 2020

et al. 2021

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Introduction: Malnutrition is a significant cause of child morbidity and mortality, and it remains a global health issue with high prevalence. Here, we carried out a bibliometric survey to provide global scientific research output on malnutrition and identify the research gaps and future research direction from published papers searched in Web of Science (WoS).Methods: A comprehensive analysis was generated by searching the WoS database. Medical Subject Headings (MeSH), was used to search terms "Malnutrition' or 'Malnourishment' or 'Nutritional Deficiency' or 'Undernutrition' or 'Nutrition Disorders.' Was used to retrieve article published in between 1900 and 2020. Only original research and review papers published in English were included in the analysis. SPSS, HistCite, Bibliometrix app." (Using R), and VOSviewer ver 1.6.6 were used for analysis. Results:Research output peak from 1972 to 2007 with 100(0.99%) articles, in 2008 to 2012 with more than 200 (1.98%) articles, while the year 2019 and 2020 had the least more than 500 (4.95%) articles per year. The United States ranked first in terms of the number of articles 1947(19.28%), followed by United Kingdom 604 (5.98%), and Brazil 412 (4.08%). In addition, our analyses revealed a significant correlation between the total number of citations Year science publications(r=0.9216, p<0.0001), and between number of countries (r=0.9219, p<0.0001), and number of Number of authors (r=0.4149, p<0.0001), and Institution (r=0.5534, p<0.0001), Journal h_index (r=0.6927, p<0.0001), and Journal impact factors (r=0.6364, p<0.0544). Conclusion:This bibliometric analysis provides insights into the global overview on the annual trend of the global malnutrition research output, institution, journal, authors, and countries.

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Section: Discussionsupporting

confidence: 86%

Malnutrition Research Output: A Bibliometric Analysis for articles Index in Web of Science between 1900 and 2020

et al. 2021

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“…Twenty of these articles were randomized clinical trials, and ten of these articles were meta-analyses and systematic reviews with a level of evidence of 1 according to SIGN criteria. Suzan et al discovered a statistically significant differences between TCN but no statistically significant differences between AAS in terms of study types [24]. We found that the level of evidence did not make a significant difference in TCN and AAS when we classified and compared the articles according to the study types and level of evidence.…”

Section: Discussionmentioning

confidence: 62%

“…Gargovich et al found an increasing positive correlation between AAS and TCN in their altmetric study in the field of pediatric dentistry investigation between 2014 and 2017 [23]. Suzan et al also revealed a statistically significant positive correlation between AAS and TCN, ACpY, journal IF, and H-index in their altmetric study on malnutrition research [24]. However, Haustein et al discovered relatively weak correlation between NTs and TCN [25].…”

Section: Discussionmentioning

confidence: 98%

The relationship between citation-based metrics and Twitter in the area of age related macular degeneration research: Altmetric and bibliometric study

Koprubasi¹,

Bulut

Çelebi

2022

J CLIN MED KAZ

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Purpose: The aim of this research is to analyze the bibliometric and altmetric scores of highly cited articles in the area of age related macular degeneration (AMD) research and to assess the correlations between them. Material and methods: The data of publications in last decade were retrieved from the Web of Science Core Collection database using "age related macular degeneration" as a search term. The top 100 cited articles (T100)  list was analyzed by author name, publication year, main topic, study type, journal name, journal impact factor (IF), H-index, total citation number (TCN), average citation per year (ACpY), Altmetric attention score (AAS), and number of tweets (NTs). VOSviewer software was utilized for  visualization of  bibliometric data. Results: We discovered 16.984 articles in the last decade. The median values for TCN and AAS were 221 (IQR 178–380.75) and 13 (IQR 4-37.75), respectively in T100 list. The majority of the highly cited articles in AMD research have mainly focused on AMD treatment (n=34), especially anti-vascular endothelial growth factor therapy. However, social attention was primarily on the stem cell therapy. While AAS and NTs did not have significant correlation with TCN, they did show a significant positive correlation with ACpY. AAS and NTs showed significant positive correlation with journal IF and H-index. Conclusion: Treatment for AMD is the most interested issue in the area. Stem cell therapies are popular on social media. The interest of social media is on articles that continue to be cited over the years rather than articles with high total citations.

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“…Altmetric attention score (AAS) obtained by altmetric analysis symbolizes the effect of articles on social media. Although it is a new analysis technique, there are many studies using this non-traditional method (7).…”

Section: Introductionmentioning

confidence: 99%

Top 100 articles on vitamin D: Bibliometric versus altmetric analysis

Kanat¹,

Yavuzer²

2022

BLL

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OBJECTIVE: To analyse the main features of the top 100 (T100) most cited articles in academia and 100 most discussed articles on social media about vitamin D from 1975 to 2021 and compare bibliometric and altmetric analysis. METHODS: 'Vitamin D' was searched from the Web of Science database and Altmetric.com website, and T100 citation and altmetric lists were created, respectively. Articles in both lists were analysed in terms of study type, topic, fi rst author, publication year, citation number and altmetric attention score (AAS). Impact factor (IF) and quartile of journal, in which the articles were published was also examined. RESULTS: The article "Vitamin D Defi ciency" by Holick MF, published in the New England Journal of Medicine was the most cited article (n = 8492), original scientifi c paper was the most frequent study type in both lists. No correlation was found between AAS and citation number in both lists (r = 0.176, p = 0.081; r=0.157, p=0.119, respectively). The journals on the T100 citation list had a statistically signifi cantly higher IF than the journals in the T100 altmetric list (p < 0.001). CONCLUSION: Altmetric analysis of vitamin D is currently insuffi cient to replace traditional bibliometric analysis but can provide valuable information about the society's interest. As social media gains more importance every day in our lives, high altmetric score could affect future interests and direct studies (Tab. 6, Fig. 3, Ref.

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Comparison of attention for malnutrition research on social media versus academia: Altmetric score analysis

Cited by 8 publications

References 23 publications

Malnutrition Research Output: A Bibliometric Analysis for articles Index in Web of Science between 1900 and 2020

Malnutrition Research Output: A Bibliometric Analysis for articles Index in Web of Science between 1900 and 2020

The relationship between citation-based metrics and Twitter in the area of age related macular degeneration research: Altmetric and bibliometric study

Top 100 articles on vitamin D: Bibliometric versus altmetric analysis

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