IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i24p16659-d1000368.html
   My bibliography  Save this article

The Evaluation of Videos about Branched-Chain Amino Acids Supplements on YouTube ™ : A Multi-Approach Study

Author

Listed:
  • Elif Günalan

    (Department of Nutrition and Dietetics, Istanbul Health and Technology University, Istanbul 34025, Turkey)

  • Saadet Turhan

    (Department of Occupational Therapy, Istanbul Health and Technology University, Istanbul 34025, Turkey
    Institute of Graduate Education, Istinye University, Istanbul 34010, Turkey)

  • Betül Yıldırım Çavak

    (Department of Nutrition and Dietetics, Istanbul Health and Technology University, Istanbul 34025, Turkey)

  • İrem Kaya Cebioğlu

    (Department of Nutrition and Dietetics, Yeditepe University, Istanbul 34755, Turkey)

  • Özge Çonak

    (Department of Health Management, Beykent University, Istanbul 34398, Turkey)

Abstract

Branched-chain amino acids (BCAAs) are one of the most controversial ergogenic aids in terms of effectiveness and safety. This study aimed to evaluate the quality and reliability of BCAA supplements related to English videos on YouTube ™ and to synthesize with the sentiment–emotion analysis of comments on videos. The content analysis of the information on videos was evaluated with the use of DISCERN, Journal of American Medical Association (JAMA) benchmark criteria, and Global Quality Score (GQS). In addition, word cloud and sentiment and emotional analysis of comments in videos were performed with the R package. As a result, the mean ± standard error values of DISCERN, JAMA, and GQS scores of all videos were 29.27 ± 1.97, 1.95 ± 0.12, and 2.13 ± 0.17, respectively. It was found that advertisement-free videos have a significantly higher DISCERN and GQS score than advertisement-included videos ( p < 0.05). A moderately significant positive correlation was determined between DISCERN score of video content and the positive sentiment of video comments (rs: 0.400, p = 0.002). In conclusion, it was determined that BCAA-related YouTube ™ videos have mostly very poor quality in terms of content and that videos with higher quality may receive positive comments from viewers according to the DISCERN instrument.

Suggested Citation

  • Elif Günalan & Saadet Turhan & Betül Yıldırım Çavak & İrem Kaya Cebioğlu & Özge Çonak, 2022. "The Evaluation of Videos about Branched-Chain Amino Acids Supplements on YouTube ™ : A Multi-Approach Study," IJERPH, MDPI, vol. 19(24), pages 1-15, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16659-:d:1000368
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/24/16659/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/24/16659/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohd Shahezwan Abd Wahab & Nurfarah Nadiah Abd Hamid & Ali Omar Yassen & Mohd Javed Naim & Javed Ahamad & Nur Wahida Zulkifli & Farhana Fakhira Ismail & Muhammad Harith Zulkifli & Khang Wen Goh & Long, 2022. "How Internet Websites Portray Herbal Vitality Products Containing Eurycoma longifolia Jack : An Evaluation of the Quality and Risks of Online Information," IJERPH, MDPI, vol. 19(19), pages 1-11, September.
    2. Martin Haselmayer & Marcelo Jenny, 2017. "Sentiment analysis of political communication: combining a dictionary approach with crowdcoding," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2623-2646, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hiroki Takikawa & Takuto Sakamoto, 2020. "The moral–emotional foundations of political discourse: a comparative analysis of the speech records of the U.S. and the Japanese legislatures," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 547-566, April.
    2. Rauh, Christian, 2018. "Validating a sentiment dictionary for German political language—a workbench note," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(4), pages 319-343.
    3. Juha Koljonen & Emily Öhman & Pertti Ahonen & Mikko Mattila, 2022. "Strategic sentiments and emotions in post-Second World War party manifestos in Finland," Journal of Computational Social Science, Springer, vol. 5(2), pages 1529-1554, November.
    4. Eyal Eckhaus & Zachary Sheaffer, 2018. "Managerial hubris detection: the case of Enron," Risk Management, Palgrave Macmillan, vol. 20(4), pages 304-325, November.
    5. Wolfinger, Julia & Köhler, Ekkehard A. & Feld, Lars P. & Thomas, Tobias, 2018. "57 Channels (And Nothin On): Does TV-News on the Eurozone affect Government Bond Yield Spreads?," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181610, Verein für Socialpolitik / German Economic Association.
    6. Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    7. Shesen Guo & Ganzhou Zhang, 2020. "Using Machine Learning for Analyzing Sentiment Orientations Toward Eight Countries," SAGE Open, , vol. 10(3), pages 21582440209, August.
    8. Katja Pietrzyck & Nora Berke & Vanessa Wendel & Julia Steinhoff-Wagner & Sebastian Jarzębowski & Brigitte Petersen, 2021. "Understanding the Importance of International Quality Standards Regarding Global Trade in Food and Agricultural Products: Analysis of the German Media," Agriculture, MDPI, vol. 11(4), pages 1-20, April.
    9. Hirsch, Patrick & Feld, Lars P. & Köhler, Ekkehard A. & Thomas, Tobias, 2024. "“Whatever It Takes!” How tonality of TV-news affected government bond yield spreads during the European debt crisis," European Journal of Political Economy, Elsevier, vol. 82(C).
    10. Robert Hogenraad, 2019. "Fear in the West: a sentiment analysis using a computer-readable “Fear Index”," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1239-1261, May.
    11. Katarina Böttcher & Kerstin Lopatta, 2020. "Gender-Sensitive Language in German Annual Reports," Journal of Management and Sustainability, Canadian Center of Science and Education, vol. 8(4), pages 1-1, March.
    12. Ralf Dewenter & Uwe Dulleck & Tobias Thomas, 2020. "Does the 4th estate deliver? The Political Coverage Index and its application to media capture," Constitutional Political Economy, Springer, vol. 31(3), pages 292-328, September.
    13. Hirsch, Patrick & Köhler, Ekkehard A. & Feld, Lars P. & Thomas, Tobias, 2020. ""Whatever it takes!": How tonality of TV-news affects government bond yield spreads during crises," Freiburg Discussion Papers on Constitutional Economics 20/9, Walter Eucken Institut e.V..
    14. Hugo Oriola & Matthieu Picault, 2023. "Opportunistic Political Central Bank Coverage: Does media coverage of ECB's Monetary Policy Impacts German Political Parties' Popularity?," EconomiX Working Papers 2023-30, University of Paris Nanterre, EconomiX.
    15. Robert Hogenraad, 2021. "The way of visionaries: foresight and imagination, computed," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1631-1660, October.
    16. Zobel, Malisa & Lehmann, Pola, 2018. "Positions and saliency of immigration in party manifestos: A novel dataset using crowd coding," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 57(4), pages 1056-1083.
    17. Dimitrios Kydros & Maria Argyropoulou & Vasiliki Vrana, 2021. "A Content and Sentiment Analysis of Greek Tweets during the Pandemic," Sustainability, MDPI, vol. 13(11), pages 1-21, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16659-:d:1000368. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.