Journal of Cyberspace Studies

Journal of Cyberspace Studies

Little digital natives and the public moral order of Persian social media

Document Type : Original article

Authors
1 Department of Communication Sciences, Faculty of Social Sciences, University of Tehran, Tehran, Iran.
2 Department of International Relations, Graduate School of Social Sciences and Humanities, Koç University, Istanbul, Turkiye.
Abstract
Background: Although the "digital native" has been empirically discredited as a scientific category, it survives as a folk figure through which adults register wonder and alarm at children's platform lives. Research on children and the internet has relied largely on Western, survey-based studies of children's experiences and parents' reported concerns, or on episodic moral panics amplified by professional media.
Aims: This study maps how Persian-language Twitter users publicly construct the intersection of children and the internet, examining the temporal architecture of the discourse across the September 2022 blocking of Instagram in Iran, its thematic structure, its frames of concern and their gendering, and the engagement dynamics that determine which talk travels.
Methodology: A corpus of 1,467 Persian tweets posted by 1,385 accounts between February 2021 and May 2025 was analyzed by combining non-negative matrix factorization topic modeling (benchmarked against LDA and a co-word network decomposition), dictionary-based frame analysis, PELT change-point detection, and negative binomial engagement regressions, with the full corpus closely read and all excerpts translated by the author.
Findings: The dominant genre is lateral family surveillance: young adults publicly exhibiting the online conduct of younger relatives, with an exact child age stated in 31.6% of all posts. The 2022 blocking contracted the discourse by 38% before it recovered above baseline; the children-in-protest frame briefly saturated the corpus and then evaporated. Concern is sharply gendered, 96% of sexualization posts and 88% of child-influencer posts are girl-marked, the influencer economy is the only growing frame, and state child-protection vocabulary appears in 0.5% of posts. Kinship anecdotes drive conversational reciprocity; policy indignation does not.
Conclusion: The public moral order of Persian social media is constructed from the family outward, not from the state downward.
Keywords
Subjects

Abidin, C. (2015). “Communicative intimacies: Influencers and perceived interconnectedness”. Ada: A Journal of Gender, New Media, and Technology. 8. https://doi.org/10.7264/N3MW2FG2.
Blei, D.M.; Ng, A.Y. & Jordan, M.I. (2003). “Latent Dirichlet allocation”. Journal of Machine Learning Research. 3: 993-1022. https://doi.org/10.1162/jmlr.2003.3.4-5.993.
Blum-Ross, A. & Livingstone, S. (2017). "’Sharenting’: Parent blogging and the boundaries of the digital self”. Popular Communication. 15(2): 110-125. https://doi.org/10.1080/15405702.2016.1223300.
Cohen, S. (2011). Folk Devils and Moral Panics: The Creation of the Mods and Rockers. Routledge Classics ed.
Dal, A. & Nisbet, E.C. (2022). “Walking through firewalls: Circumventing censorship of social media and online content in a networked authoritarian context”. Social Media + Society. 8(4). https://doi.org/10.1177/20563051221137738.
Divon, T.; Annabell, T. & Goanta, C. (2026). “Children as concealed commodities: Ethnographic nuances and legal implications of kidfluencers' monetisation on TikTok”. New Media & Society. https://doi.org/10.1177/14614448241304657.
Entman, R.M. (1993). “Framing: Toward clarification of a fractured paradigm”. Journal of Communication. 43(4): 51-58. https://doi.org/10.1111/j.1460-2466.1993.tb01304.x.
Feller, G. & Burroughs, B. (2021). “Branding kidfluencers: Regulating content and advertising on YouTube”. Television & New Media. https://doi.org/10.1177/15274764211052882.
Greyson, D.; Chabot, C.; Mniszak, C. & Shoveller, J.A. (2023). “Social media and online safety practices of young parents”. Journal of Information Science. 49(5): 1344-1357. https://doi.org/10.1177/01655515211053808.
Helsper, E.J. & Eynon, R. (2013). “Digital natives: Where is the evidence?”. British Educational Research Journal. 36(3): 503-520. https://doi.org/10.1080/01411920902989227.
Kermani, H. (2023). “#MahsaAmini: Iranian Twitter activism in times of computational propaganda”. Social Movement Studies. https://doi.org/10.1080/14742837.2023.2180354.
Kermani, H. & Tafreshi, A. (2022). “Walking with Bourdieu into Twitter communities: An analysis of networked publics struggling on power in Iranian Twittersphere”. Information, Communication & Society. https://doi.org/10.1080/1369118X.2021.2021267.
Lee, D.D. & Seung, H.S. (1999). “Learning the parts of objects by non-negative matrix factorization”. Nature. 401(6755): 788-791. https://doi.org/10.1038/44565.
Livingstone, S. & Helsper, E.J. (2013). “Children, internet and risk in comparative perspective”. Journal of Children and Media. 7(1): 1-8. https://doi.org/10.1080/17482798.2012.739751.
Livingstone, S.; Mascheroni, G. & Staksrud, E. (2018). “European research on children's internet use: Assessing the past and anticipating the future”. New Media & Society. 20(3): 1103-1122. https://doi.org/10.1177/1461444816685930.
Livingstone, S. & Stoilova, M. (2021). “The 4Cs: Classifying online risk to children” (CO:RE Short Report Series on Key Topics). Leibniz-Institut für Medienforschung | Hans-Bredow-Institut. https://doi.org/10.21241/ssoar.71817.
Marwick, A.E. (2008). “To catch a predator? The MySpace moral panic”. First Monday. 13(6). https://doi.org/10.5210/fm.v13i6.2152.
Mendelsohn, J.; Budak, C. & Jurgens, D. (2021). “Modeling framing in immigration discourse on social media”. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (pp. 2219-2263). Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.naacl-main.179.
Prensky, M. (2001). “Digital natives, digital immigrants: Part 1”. On the Horizon. 9(5): 1-6. https://doi.org/10.1108/10748120110424816.
Shokrollahi, O.; Hashemi, N. & Dehghani, M. (2021). “Discourse analysis of Covid-19 in Persian Twitter social networks using graph mining and natural language processing”. arXiv. https://arxiv.org/abs/2109.00298.
van Atteveldt, W. & Peng, T.Q. (2018). “When communication meets computation: Opportunities, challenges, and pitfalls in computational communication science”. Communication Methods and Measures. 12(2-3): 81-92. https://doi.org/10.1080/19312458.2018.1458084.

Articles in Press, Accepted Manuscript
Available Online from 07 September 2026

  • Receive Date 03 July 2026
  • Revise Date 17 July 2026
  • Accept Date 18 July 2026
  • First Publish Date 07 September 2026
  • Publish Date 07 September 2026