IDEAS home Printed from https://ideas.repec.org/a/bcp/journl/v8y2024i3p2294-2310.html
   My bibliography  Save this article

Capacity to Detect Fake News: Its Relationship to the Utilization of Online Platforms of BSED Social Studies Student

Author

Listed:
  • Ricardo O. Quiñones

    (College of Education, Notre Dame of Midsayap College, Midsayap, Cotabato, Philippines)

  • Sergio D. Mahinay, JR.

    (College of Education, Notre Dame of Midsayap College, Midsayap, Cotabato, Philippines)

  • Francis Dave C. Amiler

    (College of Education, Notre Dame of Midsayap College, Midsayap, Cotabato, Philippines)

  • Amy Jazz B. Flauta

    (College of Education, Notre Dame of Midsayap College, Midsayap, Cotabato, Philippines)

  • James A. Tubongbanua

    (College of Education, Notre Dame of Midsayap College, Midsayap, Cotabato, Philippines)

Abstract

The present study investigated the capacity to detect fake news of Social Studies students and if there is a significant relationship between the respondents’ sex, year level, age as well as their utilization of online platforms. This study was conducted only at Notre Dame of Midsayap College, specifically among the BSED Social Studies students during the second semester of the Academic Year 2022-2023. The method used in this study was causal-comparative and correlational research designs with a stratified random sampling technique. The instrument used was a researcher-made questionnaire with 34 randomly selected respondents. Despite the results, the data gathered showed that the respondents have a high capacity to detect fake news because they always check the legitimacy of the article before believing the news, compare the news with those of the more trusted sources, look for evidence that will support the claim of the new, among others. The findings of this study showed that age has a weak direct or positive relationship to the capacity to detect fake news, and that relationship is not significant; that year level has a moderately direct solid or positive relationship to the capacity to detect fake news, and that relationship is highly significant. There is no significant difference in the capacity to detect fake news according to sex. Furthermore, the utilization of online platforms also has no significant relationship with the capacity to detect fake news from the respondents. Finally, there is a very weak inverse or negative relationship between the capacity to detect fake news and the utilization of online platforms.

Suggested Citation

  • Ricardo O. Quiñones & Sergio D. Mahinay, JR. & Francis Dave C. Amiler & Amy Jazz B. Flauta & James A. Tubongbanua, 2024. "Capacity to Detect Fake News: Its Relationship to the Utilization of Online Platforms of BSED Social Studies Student," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(3), pages 2294-2310, March.
    • Handle: RePEc:bcp:journl:v:8:y:2024:i:3:p:2294-2310
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijriss/Digital-Library/volume-8-issue-3/2294-2310.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijriss/articles/capacity-to-detect-fake-news-its-relationship-to-the-utilization-of-online-platforms-of-bsed-social-studies-student/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. João Pedro Baptista & Anabela Gradim, 2020. "Understanding Fake News Consumption: A Review," Social Sciences, MDPI, vol. 9(10), pages 1-22, October.
    2. Chengcheng Shao & Giovanni Luca Ciampaglia & Onur Varol & Kai-Cheng Yang & Alessandro Flammini & Filippo Menczer, 2018. "The spread of low-credibility content by social bots," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    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. John Higgins & Tarun Sabarwal, 2023. "Control and spread of contagion in networks with global effects," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 25(6), pages 1149-1187, December.
    2. Xia, Huosong & Wang, Yuan & Zhang, Justin Zuopeng & Zheng, Leven J. & Kamal, Muhammad Mustafa & Arya, Varsha, 2023. "COVID-19 fake news detection: A hybrid CNN-BiLSTM-AM model," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    3. Csaba Both & Nima Dehmamy & Rose Yu & Albert-László Barabási, 2023. "Accelerating network layouts using graph neural networks," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    4. Francisco-Javier Herrero-Gutiérrez & José-David Urchaga-Litago, 2021. "The Importance of Rumors in the Spanish Sports Press: An Analysis of News about Signings Appearing in the Newspapers Marca, As, Mundo Deportivo and Sport," Publications, MDPI, vol. 9(1), pages 1-15, February.
    5. Howell, Bronwyn E. & Potgieter, Petrus H., 2023. "AI-generated lemons: a sour outlook for content producers?," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 277971, International Telecommunications Society (ITS).
    6. Wentao Xu & Kazutoshi Sasahara, 2022. "Characterizing the roles of bots on Twitter during the COVID-19 infodemic," Journal of Computational Social Science, Springer, vol. 5(1), pages 591-609, May.
    7. John Higgins & Tarun Sabarwal, 2021. "Control and Spread of Contagion in Networks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202111, University of Kansas, Department of Economics.
    8. Suzanne Elayan & Martin Sykora, 2024. "Digital intermediaries in pandemic times: social media and the role of bots in communicating emotions and stress about Coronavirus," Journal of Computational Social Science, Springer, vol. 7(3), pages 2481-2504, December.
    9. Jiexun Li & Xiaohui Chang, 2023. "Combating Misinformation by Sharing the Truth: a Study on the Spread of Fact-Checks on Social Media," Information Systems Frontiers, Springer, vol. 25(4), pages 1479-1493, August.
    10. Dion Hoe‐Lian Goh, 2024. "“He looks very real”: Media, knowledge, and search‐based strategies for deepfake identification," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 75(6), pages 643-654, June.
    11. Andrey Dmitriev & Victor Dmitriev & Stepan Balybin, 2019. "Self-Organized Criticality on Twitter: Phenomenological Theory and Empirical Investigation Based on Data Analysis Results," Complexity, Hindawi, vol. 2019, pages 1-16, December.
    12. Gaetano Lisi, 2023. "Online disinformation: an economic analysis," Economics and Business Letters, Oviedo University Press, vol. 12(4), pages 266-276.
    13. Vibha Sharma & Fatema Sultana & Sohaib Alam & Sameena Banu, 2024. "Trolling as a Disruptive Tool for Human Rights Violations: An Exploration of the Challenges Faced by Performance Artists," World Journal of English Language, Sciedu Press, vol. 14(4), pages 411-411, July.
    14. Lynnette Hui Xian Ng & Ian Kloo & Samantha Clark & Kathleen M. Carley, 2024. "An exploratory analysis of COVID bot vs human disinformation dissemination stemming from the Disinformation Dozen on Telegram," Journal of Computational Social Science, Springer, vol. 7(1), pages 695-720, April.
    15. Mohammad Daradkeh, 2022. "Analyzing Sentiments and Diffusion Characteristics of COVID-19 Vaccine Misinformation Topics in Social Media: A Data Analytics Framework," International Journal of Business Analytics (IJBAN), IGI Global, vol. 9(3), pages 1-22, July.
    16. Onur Varol & Ismail Uluturk, 2020. "Journalists on Twitter: self-branding, audiences, and involvement of bots," Journal of Computational Social Science, Springer, vol. 3(1), pages 83-101, April.
    17. Riccardo Gallotti & Francesco Valle & Nicola Castaldo & Pierluigi Sacco & Manlio De Domenico, 2020. "Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics," Nature Human Behaviour, Nature, vol. 4(12), pages 1285-1293, December.
    18. Cheng, Chun & Luo, Yun & Yu, Changbin, 2020. "Dynamic mechanism of social bots interfering with public opinion in network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    19. Menghan Zhang & Xue Qi & Xinyan Liu & Ke Zhang, 2024. "Who Leads? Who Follows? Exploring Agenda Setting by Media, Social Bots and Public in the Discussion of the 2022 South Korean Presidential Election," SAGE Open, , vol. 14(2), pages 21582440241, May.
    20. Dorsaf Sallami & Esma Aïmeur, 2025. "Exploring beyond detection: a review on fake news prevention and mitigation techniques," Journal of Computational Social Science, Springer, vol. 8(1), pages 1-38, February.

    More about this item

    Statistics

    Access and download statistics

    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:bcp:journl:v:8:y:2024:i:3:p:2294-2310. 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: Dr. Pawan Verma (email available below). General contact details of provider: https://rsisinternational.org/journals/ijriss/ .

    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.