Mapping the Landscape of Social Media Literacy Research: A Bibliometric Analysis of Scopus-Indexed Publications (2005–2026)

Authors

Nurhafizah Azizan

Faculty of Information Science, Universiti Teknologi MARA (UiTM) Johor (Malaysia)

Aflah Isa

Faculty of Business and Management, Universiti Teknologi MARA (UiTM) Johor (Malaysia)

Article Information

DOI: 10.47772/IJRISS.2026.100800504

Subject Category: Management

Volume/Issue: 10/8 | Page No: 7763-7779

Publication Timeline

Submitted: 2026-08-22

Accepted: 2026-08-27

Published: 2026-09-10

Abstract

Social media literacy has emerged as a distinct construct in understanding how individuals navigate misinformation, algorithmic content curation, and platform-mediated social life. Studies on this topic have grown rapidly. However, existing bibliometric work has addressed the broader construct of digital media literacy rather than social media literacy specifically, leaving the latter's intellectual structure unmapped. This study addresses that gap through a bibliometric analysis of 215 Scopus-indexed documents published between 2010 and 2026. Data were retrieved through exact-phrase matching on the Title, Abstract, and Keywords fields and refined using explicit inclusion and exclusion criteria and a documented screening procedure. VOSviewer was used to construct keyword co-occurrence and country co-authorship networks with temporal overlays. The field records a compound annual growth rate of 28.9% between 2010 and 2025, with 72.1% of all output published from 2020 onward. Twenty-five countries met the three-document threshold. The United States leads output with 61 documents, yet records an average normalised citation score of 0.99, at the world average, while Belgium (3.14), Nigeria (2.74), and China (2.31) achieve higher normalised impact from smaller outputs. Malaysia ranks third with 16 documents and collaborates almost exclusively with Global South partners. Keyword co-occurrence analysis identified six thematic clusters, of which the two largest concern conceptual foundations and adolescent well-being. Contrary to the prominence of misinformation in public discourse, the intellectual centre of the field is adolescent psychosocial outcomes, appearance and well-being themes together account for 152 of 365 keyword occurrences. Temporal analysis shows movement from pedagogy-focused research before 2020 toward population- and outcome-focused research from 2023, with algorithmic literacy recording the most recent average publication year (2025.0) despite appearing in only three documents.

Keywords

Social Media Literacy, Bibliometric Analysis, VOSviewer, Adolescent Well-being, Scopus

Downloads

References

1. Bahlamar, A. R. U. (2024). Digital media literacy in scholarly discourse: A bibliometric analysis of Scopus-indexed publications. Khizanah al-Hikmah, 12(2), 253–266. https://doi.org/10.24252/kah.v12i2a3 [Google Scholar] [Crossref]

2. Bakshy, E., Messing, S., & Adamic, L. A. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130–1132. https://doi.org/10.1126/science.aaa1160 [Google Scholar] [Crossref]

3. Balakrishnan, V. (2024). Socio-demographic predictors for misinformation sharing and authenticating amidst the COVID-19 pandemic among Malaysian young adults. Information Development, 40(2), 319–331. https://doi.org/10.1177/02666669221118922 [Google Scholar] [Crossref]

4. Brodsky, J. E., Zomberg, D., Powers, K. L., & Brooks, P. J. (2020). Assessing and fostering college students’ algorithm awareness across online contexts. Journal of Media Literacy Education, 12(3), 43–57. https://doi.org/10.23860/JMLE-2020-12-3-5 [Google Scholar] [Crossref]

5. Cho, H., Cannon, J., Lopez, R., & Li, W. (2024). Social media literacy: A conceptual framework. New Media & Society, 26(2), 941–960. https://doi.org/10.1177/14614448211068530 [Google Scholar] [Crossref]

6. Dogruel, L., Facciorusso, D., & Stark, B. (2022). ‘I’m still the master of the machine.’ Internet users’ awareness of algorithmic decision-making and their perception of its effect on their autonomy. Information, Communication & Society, 25(9), 1311–1332. https://doi.org/10.1080/1369118X.2020.1863999 [Google Scholar] [Crossref]

7. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070 [Google Scholar] [Crossref]

8. Gordon, C. S., Rodgers, R. F., Slater, A. E., McLean, S. A., Jarman, H. K., & Paxton, S. J. (2020). A cluster randomized controlled trial of the SoMe social media literacy body image and wellbeing program for adolescent boys and girls: Study protocol. Body Image, 33, 27–37. https://doi.org/10.1016/j.bodyim.2020.02.003 [Google Scholar] [Crossref]

9. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003 [Google Scholar] [Crossref]

10. Livingstone, S. (2014). Developing social media literacy: How children learn to interpret risky opportunities on social network sites. Communications, 39(3), 283–303. https://doi.org/10.1515/commun-2014-0113 [Google Scholar] [Crossref]

11. McManus, C., Baeta Neves, A. A., Finan, T. J., Pimentel, F., Pimentel, D., & Schleicher, R. T. (2024). The South-South dimension in international research collaboration. Anais da Academia Brasileira de Ciências, 96(3). https://doi.org/10.1590/0001-3765202420230942 [Google Scholar] [Crossref]

12. Paxton, S. J., McLean, S. A., & Rodgers, R. F. (2022). My critical filter buffers your app filter: Social media literacy as a protective factor for body image. Body Image, 40, 158–164. https://doi.org/10.1016/j.bodyim.2021.12.009 [Google Scholar] [Crossref]

13. Pellegrino, A., Stasi, A., & Bhatiasevi, V. (2022). Research trends in social media addiction and problematic social media use: A bibliometric analysis. Frontiers in Psychiatry, 13, 1017506. https://doi.org/10.3389/fpsyt.2022.1017506 [Google Scholar] [Crossref]

14. Polanco-Levicán, K., & Salvo-Garrido, S. (2022). Understanding social media literacy: A systematic review of the concept and its competences. International Journal of Environmental Research and Public Health, 19(14), 8807. https://doi.org/10.3390/ijerph19148807 [Google Scholar] [Crossref]

15. Schreurs, L., & Vandenbosch, L. (2021). Introducing the Social Media Literacy (SMILE) model with the case of the positivity bias on social media. Journal of Children and Media, 15(3), 320–337. https://doi.org/10.1080/17482798.2020.1809481 [Google Scholar] [Crossref]

16. Schreurs, L., Meier, A., & Vandenbosch, L. (2023). Exposure to the positivity bias and adolescents’ differential longitudinal links with social comparison, inspiration and envy depending on social media literacy. Current Psychology, 42(32), 28221–28241. https://doi.org/10.1007/s12144-022-03893-3 [Google Scholar] [Crossref]

17. Tamplin, N. C., McLean, S. A., & Paxton, S. J. (2018). Social media literacy protects against the negative impact of exposure to appearance ideal social media images in young adult women but not men. Body Image, 26, 29–37. https://doi.org/10.1016/j.bodyim.2018.05.003 [Google Scholar] [Crossref]

18. U.S. Department of Health and Human Services, Office of the Surgeon General. (2023). Social media and youth mental health: The U.S. Surgeon General’s advisory. https://www.hhs.gov/surgeongeneral/reports-and-publications/youth-mental-health/social-media/index.html [Google Scholar] [Crossref]

19. Valle, N., Zhao, P., Freed, D., Gorton, K., Chapman, A. B., Shea, A. L., & Bazarova, N. N. (2025). Towards a critical framework of social media literacy: A systematic literature review. Review of Educational Research, 95(4), 701–746. https://doi.org/10.3102/00346543241247224 [Google Scholar] [Crossref]

20. van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3 [Google Scholar] [Crossref]

21. Wang, M. L., Togher, K., Griffiths, R., & Lin, T.-K. (2024). Health misinformation on social media and adolescent health. JAMA Pediatrics, 178(2), 109–110. https://doi.org/10.1001/jamapediatrics.2023.5282 [Google Scholar] [Crossref]

22. Wei, L., Gong, J., Xu, J., Zainal Abidin, N. E., & Apuke, O. D. (2023). Do social media literacy skills help in combating fake news spread? Modelling the moderating role of social media literacy skills in the relationship between rational choice factors and fake news sharing behaviour. Telematics and Informatics, 76, 101910. https://doi.org/10.1016/j.tele.2022.101910 [Google Scholar] [Crossref]

23. Wu, D., Sukumaran, S., Zhi, X., Zhou, W., Li, L., & You, H. (2025). Categories, themes and research evolution of the study of digital literacy: A bibliometric analysis. Education and Information Technologies, 30(4), 4907–4931. https://doi.org/10.1007/s10639-024-12955-x [Google Scholar] [Crossref]

24. Yu, Z., Sukjairungwattana, P., & Xu, W. (2023). Bibliometric analyses of social media for educational purposes over four decades. Frontiers in Psychology, 13, 1061989. https://doi.org/10.3389/fpsyg.2022.1061989 [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles