Uso Problemático de Mídias Sociais e Falta de Atenção: Uma Análise via Arquitetura de Processamento de Linguagem Natural Híbrida
Resumo
O uso problemático de mídias sociais compromete severamente funções executivas e a atenção. Para investigar esse fenômeno, propõe-se um framework analítico de identificação de padrões comportamentais. Como prova de conceito, desenvolveu-se um pipeline de Processamento de Linguagem Natural com dados do YouTube, cuja inovação reside numa arquitetura híbrida (Sentence Transformers e Large Language Models) capaz de classificar textos ruidosos com alta precisão. Ensaios preliminares via modelagem de tópicos validaram a abordagem ao extrair clusters sobre táticas de foco e neurodivergência. Conclui-se que a metodologia garante proveniência e curadoria de dados em larga escala, viabilizando datasets confiáveis para pesquisas em saúde digital. Informações Gerais.
Palavras-chave:
Uso Problemático de Mídias Sociais, Processamento de Linguagem Natural, User-Generated Content
Referências
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Côrte-Real, B., Cordeiro, C., Câmara Pestana, P., Duarte E Silva, I., and Novais, F. (2022). Addictive Potential of Social Media: A Cross Sectional Study in Portugal. Acta Médica Portuguesa, 36(3):162–166. Portugal.
Dam, V. A. T., Dao, N. G., Nguyen, D. C., Vu, T. M. T., Boyer, L., Auquier, P., Fond, G., Ho, R. C. M., Ho, C. S. H., and Zhang, M. W. B. (2023). Quality of life and mental health of adolescents: Relationships with social media addiction, Fear of Missing out, and stress associated with neglect and negative reactions by online peers. PLOS ONE, 18(6):e0286766.
De La Torre, P. G., Pérez-Verdugo, M., and Barandiaran, X. E. (2025). Attention is all they need: cognitive science and the (techno)political economy of attention in humans and machines. AI & SOCIETY.
Desai, S. and Thombre, S. (2025). User Interactions and Attention as Internet Currency: Impact on Digital Assets. In 2025 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), pages 1–6, Bengaluru, India. IEEE.
Fang, X., Yang, J., Liu, B., Wang, Y., Liao, J., and Lei, L. (2026). Exploring fear of missing out and problematic social media use among Generation Alpha: a random intercept cross-lagged panel model and cross-lagged panel network analysis. Addictive Behaviors, 172:108489.
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Munia, J. A., Tahmiduzzaman, K., Saad, I. H., Islam, M. M., Akash, A. H., and Zumma, M. T. (2025). A Study of Predicting Social Networking Sites(SNS) Media Disorder Survey Data Using a Machine Learning Approach. In 2025 International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI), pages 300–306, Erode, India. IEEE.
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Yeasmin, T. and Islam, M. M. (2026). A Data-Driven Approach to Combating Social Media Addiction: Insights from Explainable AI. In 2026 5th International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE), pages 1–6, Rajshahi, Bangladesh. IEEE.
Akter, M., Ritu, K. F., Habib, M. T., Rahman, M. S., and Ahmed, F. (2022). A Machine Learning Approach To Predict Social Media Addiction During COVID-19 Pandemic. In 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC), pages 401–405, Salem, India. IEEE.
Amirthalingam, J. and Khera, A. (2024). Understanding Social Media Addiction: A Deep Dive. Cureus.
Ayaz-Alkaya, S. and Kulakçı-Altıntaş, H. (2025). Social media addiction, nomophobia, and social anxiety among adolescents: A mediation analysis. Journal of Pediatric Nursing, 85:16–21.
Côrte-Real, B., Cordeiro, C., Câmara Pestana, P., Duarte E Silva, I., and Novais, F. (2022). Addictive Potential of Social Media: A Cross Sectional Study in Portugal. Acta Médica Portuguesa, 36(3):162–166. Portugal.
Dam, V. A. T., Dao, N. G., Nguyen, D. C., Vu, T. M. T., Boyer, L., Auquier, P., Fond, G., Ho, R. C. M., Ho, C. S. H., and Zhang, M. W. B. (2023). Quality of life and mental health of adolescents: Relationships with social media addiction, Fear of Missing out, and stress associated with neglect and negative reactions by online peers. PLOS ONE, 18(6):e0286766.
De La Torre, P. G., Pérez-Verdugo, M., and Barandiaran, X. E. (2025). Attention is all they need: cognitive science and the (techno)political economy of attention in humans and machines. AI & SOCIETY.
Desai, S. and Thombre, S. (2025). User Interactions and Attention as Internet Currency: Impact on Digital Assets. In 2025 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), pages 1–6, Bengaluru, India. IEEE.
Fang, X., Yang, J., Liu, B., Wang, Y., Liao, J., and Lei, L. (2026). Exploring fear of missing out and problematic social media use among Generation Alpha: a random intercept cross-lagged panel model and cross-lagged panel network analysis. Addictive Behaviors, 172:108489.
IBGE, editor (2025). Acesso à internet e à televisão e posse de telefone móvel celular para uso pessoal 2024. IBGE, Rio de Janeiro, RJ.
Mim, M. N., Firoz, M., Islam, M. M., Hasan, M., and Habib, M. T. (2024). A study on social media addiction analysis on the people of Bangladesh using machine learning algorithms. Bulletin of Electrical Engineering and Informatics, 13(5):3493–3502.
Munia, J. A., Tahmiduzzaman, K., Saad, I. H., Islam, M. M., Akash, A. H., and Zumma, M. T. (2025). A Study of Predicting Social Networking Sites(SNS) Media Disorder Survey Data Using a Machine Learning Approach. In 2025 International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI), pages 300–306, Erode, India. IEEE.
Roswendi, R. and Gong, X. (2025). A Cross-Cultural Study on the Impact of Social Media Usage on High School Students’ Learning. IEEE Integrated STEM Education Conference.
World Health Organization (2019). International statistical classification of diseases and related health problems (11th ed.). [link]. Acessado em: 14 maio 2026.
Yeasmin, T. and Islam, M. M. (2026). A Data-Driven Approach to Combating Social Media Addiction: Insights from Explainable AI. In 2026 5th International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE), pages 1–6, Rajshahi, Bangladesh. IEEE.
Publicado
08/09/2026
Como Citar
RIZZO, Isabelle Santiago Cardoso; LIMA FILHO, Silas.
Uso Problemático de Mídias Sociais e Falta de Atenção: Uma Análise via Arquitetura de Processamento de Linguagem Natural Híbrida. In: WORKSHOP DE TESES E DISSERTAÇÕES (WTDBD) - SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 41. , 2026, São Carlos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 314-320.
DOI: https://doi.org/10.5753/sbbd_estendido.2026.249625.
