NLP Models for Mental Health-Related Text Analysis in Brazilian University Reddit Communities
Resumo
Online communities have become important spaces for mental health discussions among university students, generating large volumes of text that are difficult to analyze manually at scale. This work investigates automated methods for analyzing emotional and relational aspects of mental health-related text in three Brazilian university Reddit communities. We employed NLP models to evaluate two dimensions: the emotional tone expressed in the text and the presence or absence of supportive social interaction. The results indicate that automated methods are suitable for scalable identification of social support behaviors, while emotional tone analysis requires greater caution and is best applied to clearly polarized expressions rather than fine-grained neutral distinctions.
Palavras-chave:
mental health, reddit, Brazilian universities, nlp, llm, emotional valence, social support
Referências
Aggarwal, V., Thukral, S., Patel, K., and Chatterjee, A. (2024). Leveraging llms for mental health: Detection and recommendations from social discussions. In 2024 IEEE/WIC Int. Conf. on Web Intel. and Intellig. Agent Tech. (WI-IAT), pages 350–354. IEEE.
Almeida, R. J. A. (2018). Leia - léxico para inferência adaptada. [link].
Atapattu, T., Herath, M., Elvitigala, C., de Zoysa, P., Gunawardana, K., Thilakaratne, M., De Zoysa, K., and Falkner, K. (2022). Emoment: An emotion annotated mental health corpus from two south asian countries. In Proceedings of the 29th International Conference on Computational Linguistics, pages 6991–7001.
Barbieri, F., Espinosa Anke, L., and Camacho-Collados, J. (2022). XLM-T: Multilingual language models in Twitter for sentiment analysis and beyond. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 258–266, Marseille, France. European Language Resources Association.
Barrett, L. F. (2017). How emotions are made: The secret life of the brain. Pan Macmillan.
Fan, Y., Fan, A., Yang, Z., and Fan, D. (2025). Global burden of mental disorders in 204 countries and territories, 1990–2021: results from the global burden of disease study 2021. BMC Psychiatry, 25(1):486.
Guo, X., Sun, Y., and Vosoughi, S. (2021). Emotion-based modeling of mental disorders on social media. In Int. Conf. on Web Intel. and Intellig. Agent Tech., pages 8–16.
Herculano, A., de Paula, T.-H., Fernandes, D., and Rego, A. (2024). DepreRedditBR: Um conjunto de dados textuais com postagens depressivas no idioma português brasileiro. In VI Dataset Showcase Workshop, pages 77–90, Porto Alegre, RS, Brasil. SBC.
House, J. (1981). Work Stress and Social Support. Addison-Wesley Series in Health Education. Addison-Wesley Publishing Company.
Hutto, C. J. and Gilbert, E. (2014). VADER: A parsimonious rule-based model for sentiment analysis of social media text. In Int. AAAI Conf. on Web and Social Media, volume 8, pages 216–225.
Inamdar, S., Chapekar, R., Gite, S., and Pradhan, B. (2023). Machine learning driven mental stress detection on reddit posts using natural language processing. Human-Centric Intelligent Systems, 3(2):80–91.
Li, Q., Li, J., and Fan, Y. (2025). Addressing mental health in university students: a call for action. Frontiers in Public Health, 13:1614999.
Low, D. M., Rumker, L., Talkar, T., Torous, J., Cecchi, G., and Ghosh, S. S. (2020). Natural language processing reveals vulnerable mental health support groups and heightened health anxiety on reddit during covid-19: Observational study. Journal of medical Internet research, 22(10):e22635.
Marques, M. C., Silva, C. O., Dallagnol, L. P., Rocha, T. C. B., and Ponciano, J. R. (2026). BrStudentMH: A Reddit dataset for mental health analysis in the Brazilian university context. In VIII Dataset Showcase Workshop. accepted.
Montejo-Ráez, A., Molina-González, M. D., Jiménez-Zafra, S. M., Ángel García-Cumbreras, M., and García-López, L. J. (2024). A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges. Computer Science Review, 53:100654.
Nandwani, P. and Verma, R. (2021). A review on sentiment analysis and emotion detection from text. Social Network Analysis and Mining, 11(1):81.
Oliveira, R. A., Véras, R. M., and Araújo, T. M. d. (2025). Assistência estudantil e promoção da saúde mental nas universidades federais brasileiras: uma revisão integrativa. Avaliação: Revista da Avaliação da Educação Superior (Campinas), 30:e025030.
Pang, B. and Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2):1–135.
Ren, L., Lin, H., Xu, B., Zhang, S., Yang, L., and Sun, S. (2021). Depression detection on reddit with an emotion-based attention network: algorithm development and validation. JMIR medical informatics, 9(7):e28754.
Ruihua, L., Hassan, N. C., Qiuxia, Z., Sha, O., and Jingyi, D. (2025). A systematic review on the impact of social support on college students’ wellbeing and mental health. Plos one, 20(7):e0325212.
Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6):1161–1178.
Sampath, K. and Durairaj, T. (2022). Data set creation and empirical analysis for detecting signs of depression from social media postings. In International Conference on Computational Intelligence in Data Science, pages 136–151. Springer.
Sweetlin, J. D., Vaisshnavi, S., Keshavan, A., and Palanisamy, R. (2025). Detection of mental illness from reddit data using deep learning and mitigation using generative ai. In 2025 Int. Conf. on Computing, Intelligence, and Application (CIACON), pages 1–8.
Times Higher Education (2025). Latin america university rankings 2026. [link]. Acesso em: 11 dez. 2025.
World Health Organization (2017). Depression and Other Common Mental Disorders: Global Health Estimates. World Health Organization, Geneva.
Almeida, R. J. A. (2018). Leia - léxico para inferência adaptada. [link].
Atapattu, T., Herath, M., Elvitigala, C., de Zoysa, P., Gunawardana, K., Thilakaratne, M., De Zoysa, K., and Falkner, K. (2022). Emoment: An emotion annotated mental health corpus from two south asian countries. In Proceedings of the 29th International Conference on Computational Linguistics, pages 6991–7001.
Barbieri, F., Espinosa Anke, L., and Camacho-Collados, J. (2022). XLM-T: Multilingual language models in Twitter for sentiment analysis and beyond. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 258–266, Marseille, France. European Language Resources Association.
Barrett, L. F. (2017). How emotions are made: The secret life of the brain. Pan Macmillan.
Fan, Y., Fan, A., Yang, Z., and Fan, D. (2025). Global burden of mental disorders in 204 countries and territories, 1990–2021: results from the global burden of disease study 2021. BMC Psychiatry, 25(1):486.
Guo, X., Sun, Y., and Vosoughi, S. (2021). Emotion-based modeling of mental disorders on social media. In Int. Conf. on Web Intel. and Intellig. Agent Tech., pages 8–16.
Herculano, A., de Paula, T.-H., Fernandes, D., and Rego, A. (2024). DepreRedditBR: Um conjunto de dados textuais com postagens depressivas no idioma português brasileiro. In VI Dataset Showcase Workshop, pages 77–90, Porto Alegre, RS, Brasil. SBC.
House, J. (1981). Work Stress and Social Support. Addison-Wesley Series in Health Education. Addison-Wesley Publishing Company.
Hutto, C. J. and Gilbert, E. (2014). VADER: A parsimonious rule-based model for sentiment analysis of social media text. In Int. AAAI Conf. on Web and Social Media, volume 8, pages 216–225.
Inamdar, S., Chapekar, R., Gite, S., and Pradhan, B. (2023). Machine learning driven mental stress detection on reddit posts using natural language processing. Human-Centric Intelligent Systems, 3(2):80–91.
Li, Q., Li, J., and Fan, Y. (2025). Addressing mental health in university students: a call for action. Frontiers in Public Health, 13:1614999.
Low, D. M., Rumker, L., Talkar, T., Torous, J., Cecchi, G., and Ghosh, S. S. (2020). Natural language processing reveals vulnerable mental health support groups and heightened health anxiety on reddit during covid-19: Observational study. Journal of medical Internet research, 22(10):e22635.
Marques, M. C., Silva, C. O., Dallagnol, L. P., Rocha, T. C. B., and Ponciano, J. R. (2026). BrStudentMH: A Reddit dataset for mental health analysis in the Brazilian university context. In VIII Dataset Showcase Workshop. accepted.
Montejo-Ráez, A., Molina-González, M. D., Jiménez-Zafra, S. M., Ángel García-Cumbreras, M., and García-López, L. J. (2024). A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges. Computer Science Review, 53:100654.
Nandwani, P. and Verma, R. (2021). A review on sentiment analysis and emotion detection from text. Social Network Analysis and Mining, 11(1):81.
Oliveira, R. A., Véras, R. M., and Araújo, T. M. d. (2025). Assistência estudantil e promoção da saúde mental nas universidades federais brasileiras: uma revisão integrativa. Avaliação: Revista da Avaliação da Educação Superior (Campinas), 30:e025030.
Pang, B. and Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2):1–135.
Ren, L., Lin, H., Xu, B., Zhang, S., Yang, L., and Sun, S. (2021). Depression detection on reddit with an emotion-based attention network: algorithm development and validation. JMIR medical informatics, 9(7):e28754.
Ruihua, L., Hassan, N. C., Qiuxia, Z., Sha, O., and Jingyi, D. (2025). A systematic review on the impact of social support on college students’ wellbeing and mental health. Plos one, 20(7):e0325212.
Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6):1161–1178.
Sampath, K. and Durairaj, T. (2022). Data set creation and empirical analysis for detecting signs of depression from social media postings. In International Conference on Computational Intelligence in Data Science, pages 136–151. Springer.
Sweetlin, J. D., Vaisshnavi, S., Keshavan, A., and Palanisamy, R. (2025). Detection of mental illness from reddit data using deep learning and mitigation using generative ai. In 2025 Int. Conf. on Computing, Intelligence, and Application (CIACON), pages 1–8.
Times Higher Education (2025). Latin america university rankings 2026. [link]. Acesso em: 11 dez. 2025.
World Health Organization (2017). Depression and Other Common Mental Disorders: Global Health Estimates. World Health Organization, Geneva.
Publicado
08/09/2026
Como Citar
ROCHA, Tiago C. B.; DALLAGNOL, Leonardo P.; MARQUES, Maicon C.; SILVA, Camila O.; VILAÇA, Júlia O.; PONCIANO, Jean R..
NLP Models for Mental Health-Related Text Analysis in Brazilian University Reddit Communities. In: DATA SCIENCE FOR SOCIAL GOOD BRAZILIAN WORKSHOP (DS4SG) - SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 41. , 2026, São Carlos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 503-512.
DOI: https://doi.org/10.5753/sbbd_estendido.2026.249683.
