A framework for controversial political topics identification using Twitter data (2023)
Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DE TEXTO, EMOÇÕES, PORTUGUÊS DO BRASIL, MÍDIAS SOCIAIS
ABNT
SAKIYAMA, Kenzo et al. A framework for controversial political topics identification using Twitter data. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-45392-2_19. Acesso em: 23 ago. 2024. , 2023APA
Sakiyama, K., Rodrigues, L. de S., Nogueira, B. M., Matsubara, E. T., & Romero, R. A. F. (2023). A framework for controversial political topics identification using Twitter data. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-45392-2_19NLM
Sakiyama K, Rodrigues L de S, Nogueira BM, Matsubara ET, Romero RAF. A framework for controversial political topics identification using Twitter data [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14197 283-298.[citado 2024 ago. 23 ] Available from: https://doi.org/10.1007/978-3-031-45392-2_19Vancouver
Sakiyama K, Rodrigues L de S, Nogueira BM, Matsubara ET, Romero RAF. A framework for controversial political topics identification using Twitter data [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14197 283-298.[citado 2024 ago. 23 ] Available from: https://doi.org/10.1007/978-3-031-45392-2_19