Measuring the impact of readability features in fake news Detection (2020)
Source: Proceedings. Conference titles: Conference on Language Resources and Evaluation - LREC. Unidade: ICMC
Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL, LINGUÍSTICA COMPUTACIONAL, NOTÍCIA, PORTUGUÊS DO BRASIL
ABNT
SANTOS, Roney Lira de Sales et al. Measuring the impact of readability features in fake news Detection. 2020, Anais.. Paris: European Language Resources Association, 2020. Disponível em: https://www.aclweb.org/anthology/2020.lrec-1.176. Acesso em: 31 out. 2024.APA
Santos, R. L. de S., Wick-Pedro, G., Leal, S. E., Vale, O. A., Pardo, T. A. S., Bontcheva, K., & Scarton, C. E. (2020). Measuring the impact of readability features in fake news Detection. In Proceedings. Paris: European Language Resources Association. Recuperado de https://www.aclweb.org/anthology/2020.lrec-1.176NLM
Santos RL de S, Wick-Pedro G, Leal SE, Vale OA, Pardo TAS, Bontcheva K, Scarton CE. Measuring the impact of readability features in fake news Detection [Internet]. Proceedings. 2020 ;[citado 2024 out. 31 ] Available from: https://www.aclweb.org/anthology/2020.lrec-1.176Vancouver
Santos RL de S, Wick-Pedro G, Leal SE, Vale OA, Pardo TAS, Bontcheva K, Scarton CE. Measuring the impact of readability features in fake news Detection [Internet]. Proceedings. 2020 ;[citado 2024 out. 31 ] Available from: https://www.aclweb.org/anthology/2020.lrec-1.176