Discurso de Influenciadores Voltados ao Público Infantojuvenil no Instagram: Uma Comparação Brasil e Estados Unidos
Resumo
Dada a crescente influência de criadores de conteúdo direcionados a crianças e adolescentes, torna-se fundamental compreender como esses agentes estruturam seus discursos nas mídias sociais. Este trabalho apresenta uma análise comparativa e multinível do discurso de influenciadores no Instagram no Brasil e nos Estados Unidos, com base na análise de legendas e transcrições de vídeos públicos. Investigamos o uso de emojis e hashtags, atributos psicolinguísticos, tópicos semânticos, níveis de toxicidade e os valores humanos expressos no conteúdo. Os resultados revelam padrões consistentes de autoapresentação, entretenimento e publicidade em ambos os países, além de diferenças culturais claras. No Brasil, destacam-se referências à família, religiosidade e valores tradicionais, enquanto nos Estados Unidos predominam estratégias de marca pessoal e valores associados a prestígio social e prazer. Adicionalmente, as transcrições apresentam maior prevalência de conteúdo sensível, enquanto as legendas concentram estratégias de engajamento.
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Alqahtani, S., Yafooz, W., Alsaeedi, A., Syed, L., and Alluhaibi, R. (2023). Children’s Safety on YouTube: A Systematic Review. Applied Sciences, 13:4044.
Alshamrani, S., Abusnaina, A., Abuhamad, M., Nyang, D., and Mohaisen, D. (2021). Hate, Obscenity, and Insults: Measuring the Exposure of Children to Inappropriate Comments in YouTube. In Proc. Web Conference.
Amalia, D., Warto, W., Pitana, T. S., and Habsari, S. K. (2024). Kidfluencers: The Rise of Capitalizing Kids as Instagram Microcelebrities in Indonesia. In Proc. ICCoLLiC.
Archer, C. and Delmo, K. (2023). Play Is a Child’s Work(on Instagram):A Case Study of the Use of Children as Paid Social Media Influencers to Market Toys. M/CJournal, 26.
Archer, C. and Delmo, K. (2025). Children’s ‘playbour’ as Influencers on Social Media:An Investigation Into the Legal and Ethical Issues Surrounding Kidfluencers. RCRP, 11.
Balaban, D., Mucundorfeanu, M., and Mureşan, L. (2022). Adolescents’ Understanding of the Model of Sponsored Content of Social Media Influencer Instagram Stories. JMC, 10:305–316.
Borenstein, N., Arora, A., Kaffee, L.-A., and Augenstein, I. (2025). Investigating Human Values in Online Communities. In Proc. NAACL.
Bouchardet, C., Gonçalves, K., Passaro, L., Almeida, J., and Marques-Neto, H. (2025). Call2Go: A Cross-Platform Strategy Of Kids Online Social Media Influencers. In Proc. WebMedia.
Caetano, J. A., Bouchardet, C. C., and Marques-Neto, H. T. (2023). Identifying and Characterizing Child Advertising on Instagram. In Proc. OASIS.
Carvalho, F., Rodrigues, R. G., Santos, G. A. S., Cruz, P., Ferrari, L., and Guedes, G. P. (2019). Evaluating the Brazilian Portuguese Version of the 2015 LIWC Lexicon with Sentiment Analysis in Social Networks. In Proc. BraSNAM.
Coates, A., Hardman, C., Halford, J., Christiansen, P., and Boyland, E. (2019). Social Media Influencer Marketing and Children’s Food Intake:A Randomized Trial. Journal of Pediatrics, 143.
Common Sense (2025). The Common Sense Census: Media Use by Kids Zero to Eight.
De Veirman, M., Hudders, L., and Nelson, M. (2019). What Is Influencer Marketing and How Does It Target Children? A Review and Direction for Future Research. Frontiers in Psychology, Volume 10.
Gonçalves, K., Soriano, F., Vimieiro, R., Marques-Neto, H., and Almeida, J. (2025). Caracterização das Recomendações de Streams na Twitch para o Público Infantil. In Proc. WebMedia.
Gonzalez, A., Akgün, I., and Vandenbosch, L. (2025). The Values of Fame: Exploring the Visual and Textual Representations of Basic Values in Influencers’ Instagram Content. Social Media + Society, 11.
Gonçalves, K. C., Soriano, F., Marques-Neto, H. T., and Almeida, J. M. (2026). Potential Exposure of Kids to Age-Inappropriate Content on Twitch: A Comparative Cross-Country Study. ASONAM, 16.
Grootendorst, M. (2022). BERTopic: Neural Topic Modeling with a Class-based TF-IDF Procedure. arXiv preprint arXiv:2203.05794.
Human Rights Watch (2025). Brazil Passes Landmark Law to Protect Children Online.
Joulin, A., Grave, E., Bojanowski, P., and Mikolov, T. (2017). Bag of Tricks for Efficient Text Classification. In Lapata, M., Blunsom, P., and Koller, A., editors, Proc. EACL.
Kaushal, R., Saha, S., Bajaj, P., and Kumaraguru, P. (2016). KidsTube: Detection, Characterization and Analysis of Child Unsafe Content & Promoters on YouTube. In Proc. PST.
Lees, A., Tran, V. Q., Tay, Y., Sorensen, J., Gupta, J., Metzler, D., and Vasserman, L. (2022). A New Generation of Perspective API: Efficient Multilingual Character-level Transformers. In Proc. SIGKDD.
McGuire, M. and Larson-Hall, J. (2025). Assessing Whisper Automatic Speech Recognition and WER Scoring for Elicited Imitation:Steps Toward Automation. RMAL, 4.
Nogara, G., Pierri, F., Cresci, S., Luceri, L., Törnberg, P., and Giordano, S. (2025). Toxic Bias: Perspective API Misreads German as More Toxic. In Proc. ICWSM.
Papadamou, K., Papasavva, A., Zannettou, S., Blackburn, J., Kourtellis, N., Leontiadis, I., Stringhini, G., and Sirivianos, M. (2019). Disturbed YouTube for Kids: Characterizing and Detecting Inappropriate Videos Targeting Young Children. In Proc. ICWSM.
Pennebaker, J. W., Boyd, R. L., Jordan, K., and Blackburn, K. (2015). The Development and Psychometric Properties of LIWC2015. Austin, TX: University of Texas at Austin.
Radford, A., Kim, J. W., Xu, T., Brockman, G., McLeavey, C., and Sutskever, I. (2023). Robust Speech Recognition Via Large-scale Weak Supervision. In Proc. ICML.
Rasmussen, E., Riggs, R. E., and Sauermilch, W. (2021). Kidfluencer Exposure, Materialism, and U.S. Tweens’ Purchase of Sponsored Products. JCM, 16:1–10.
Schwartz, S. (2012). An Overview of the Schwartz Theory of Basic Values. ORPC, 2:11.
Sokolova, K. and Kefi, H. (2020). Instagram and YouTube Bloggers Promote it, Why Should I Buy? How Credibility and Parasocial Interaction Influence Purchase Intentions. JRCS, 53:101742.
van der Meer, M., Vossen, P., Jonker, C. M., and Murukannaiah, P. K. (2023). Do Differences in Values Influence Disagreements in Online Discussions? In Proc. EMNLP.
Violet, C., Boyé, A., Dubois, S., Edgar, G. J., Oh, E. S., Stuart-Smith, R. D., and Marzloff, M. P. (2025). Leveraging citizen science to classify and track benthic habitat states: An unsupervised umap-hdbscan pipeline applied to the global reef life survey dataset. Ecological Informatics, 86:103058.
Wasserman, L. (2004). All of statistics: a concise course in statistical inference. Springer.
Publicado
19/07/2026
Como Citar
RIBEIRO, Murilo U.; GONÇALVES, Kênia C.; M. FILHO, Renato; LIMA, Tomaz C.; GONÇALVES, Marcos A.; ALMEIDA, Jussara M..
Discurso de Influenciadores Voltados ao Público Infantojuvenil no Instagram: Uma Comparação Brasil e Estados Unidos. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 15. , 2026, Gramado/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 122-135.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2026.23440.
