Emojis e Discurso de Ódio no Contexto Brasileiro: Uma Análise a Partir de Diferentes Plataformas Sociais
Resumo
A massificação das plataformas sociais no Brasil consolidou ambientes como Instagram, YouTube e Twitter/X como espaços centrais de interação, mas também de disseminação de discurso de ódio. Embora haja avanços em abordagens computacionais para sua detecção, o papel dos emojis ainda é pouco explorado no cenário nacional. Este trabalho investiga a relação entre emojis e discurso de ódio em português (PT-BR) a partir de um conjunto de mais de 30 mil mensagens rotuladas, analisadas com técnicas de Processamento de Linguagem Natural (PLN). Os resultados indicam que alguns emojis apresentam associação consistente com o discurso de ódio, enquanto outros variam conforme o contexto. Essas descobertas destacam o potencial dos emojis como sinal complementar em modelos automáticos de detecção. Atenção! Este trabalho e os dados referenciados contêm exemplos de linguagem potencialmente ofensiva e odiosa.Referências
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Silva, S. C. and Serapião, A. B. (2018). Detecção de discurso de ódio em português usando cnn combinada a vetores de palavras. In Symposium on Knowledge Discovery, Mining and Learning (KDMiLe), pages 1–8.
Trajano, D., Bordini, R. H., and Vieira, R. (2024). Olid-br: offensive language identification dataset for brazilian portuguese. Language Resources and Evaluation, 58(4):1263–1289.
Althobaiti, M. J. (2022). Bert-based approach to arabic hate speech and offensive language detection in twitter: exploiting emojis and sentiment analysis. International Journal of Advanced Computer Science and Applications, 13(5).
Bertot, J. C., Jaeger, P. T., and Hansen, D. (2012). The impact of polices on government social media usage: Issues, challenges, and recommendations. Government information quarterly, 29(1):30–40.
Biere, S., Bhulai, S., and Analytics, M. B. (2018). Hate speech detection using natural language processing techniques. Master Business AnalyticsDepartment of Mathematics Faculty of Science.
Braga, M. L. P., Nakamura, F. G., and Nakamura, E. F. (2020). Criação e caracterização de um corpus de discurso sexista em português. In Brazilian Workshop on Social Network Analysis and Mining (BraSNAM), pages 97–107.
Caetano, J., Guimarães, S., Araújo, M. M., Silva, M., Reis, J. C., Silva, A. P., Benevenuto, F., and Almeida, J. M. (2022). Characterizing early electoral advertisements on twitter: A brazilian case study. In International Conference on Social Informatics, pages 257–272.
de Freitas Melo, P., Kansaon, D., Couto, J. M., Reis, J. C., and Benevenuto, F. (2025). A sticker is worth a thousand words: Characterizing the use and abuse of stickers on whatsapp political groups in brazil. In Proc. of the Int’l AAAI Conference on Web and Social Media, volume 19, pages 1210–1223.
de Oliveira, F. R., Reis, V. D., and Ebecken, N. F. F. (2024). Detecting hate speech on brazilian social media: New dataset and analysis. In Ibero-Latin American Congress on Computational Methods in Engineering (CILAMCE).
De Pelle, R. P. and Moreira, V. P. (2017). Offensive comments in the brazilian web: a dataset and baseline results. In Brazilian Workshop on Social Network Analysis and Mining (BRASNAM), pages 510–519.
de Santana, V. F., Melo-Solarte, D. S., de Almeida Neris, V. P., de Miranda, L. C., and Baranauskas, M. C. C. (2009). Redes sociais online: desafios e possibilidades para o contexto brasileiro. In Seminário Integrado de Software e Hardware (SEMISH), pages 339–353.
Fortuna, P., da Silva, J. R., Wanner, L., Nunes, S., et al. (2019). A hierarchically-labeled portuguese hate speech dataset. In Proceedings of the third workshop on abusive language online, pages 94–104.
Fortuna, P. and Nunes, S. (2018). A survey on automatic detection of hate speech in text. ACM Computing Surveys, 51(4):85:1–85:30.
Grosz, P. G., Greenberg, G., De Leon, C., and Kaiser, E. (2023). A semantics of face emoji in discourse. Linguistics and Philosophy, 46(4):905–957.
Grover, V. and Banati, H. (2024). An attention approach to emoji focused sarcasm detection. Heliyon, 10(17):e36398.
Guimarães, S., Silva, M., Caetano, J., Araújo, M., dos Reis, J. C. S., da Silva, A. P. C., Benevenuto, F., and Almeida, J. M. (2022). Análise de propagandas eleitorais antecipadas no twitter. In Brazilian Workshop on Social Network Analysis and Mining (BraSNAM).
Ibrohim, M. O., Setiadi, M. A., and Budi, I. (2019). Identification of hate speech and abusive language on indonesian twitter using the word2vec, part of speech and emoji features. In Proceedings of the International Conference on Advanced Information Science and System (AISS), pages 1–5.
Leite, J. A., Silva, D., Bontcheva, K., and Scarton, C. (2020). Toxic language detection in social media for brazilian portuguese: New dataset and multilingual analysis. In Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, pages 914–924.
Moreira, L. S., Gibrim, P. T. M., Rocha, L., and Reis, J. C. S. (2026). Anatomy of data repositories for the analysis and detection of toxicity in portuguese. In Proceedings of the International Conference on Computational Processing of Portuguese (PROPOR) - Vol. 1. Association for Computational Lingustics.
Pinto, S. L., Campolina, J. J., Sena, J. P. M., Félix, G., Ferreira, L. N., and Reis, J. C. (2024). Caracterização e predição de usuários tóxicos no twitter/x durante as eleições brasileiras de 2022. In Brazilian Workshop on Social Network Analysis and Mining (BraSNAM), pages 61–74.
Rodrigues, F. F. (2025). A morfologia dos emojis: explorando a linguagem visual na comunicação digital em inglês. Trabalho de Conclusão de Curso. Universidade Estadual do Piauí.
Salles, I., Vargas, F., and Benevenuto, F. (2025). Hatebrxplain: A benchmark dataset with human-annotated rationales for explainable hate speech detection in brazilian portuguese. In Proceedings of the International Conference on Computational Linguistics (COLING), pages 6659–6669.
Silva, S. C. and Serapião, A. B. (2018). Detecção de discurso de ódio em português usando cnn combinada a vetores de palavras. In Symposium on Knowledge Discovery, Mining and Learning (KDMiLe), pages 1–8.
Trajano, D., Bordini, R. H., and Vieira, R. (2024). Olid-br: offensive language identification dataset for brazilian portuguese. Language Resources and Evaluation, 58(4):1263–1289.
Publicado
19/07/2026
Como Citar
FERNANDES, Thúlio M. O.; GIBRIM, Paula T. M.; REIS, Julio C. S..
Emojis e Discurso de Ódio no Contexto Brasileiro: Uma Análise a Partir de Diferentes Plataformas Sociais. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 15. , 2026, Gramado/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 136-149.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2026.23590.
