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
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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: 21 jan. 2026.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 2026 jan. 21 ] 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 2026 jan. 21 ] Available from: https://www.aclweb.org/anthology/2020.lrec-1.176
