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- W2981566181 abstract "As Brazil faced one of its most important elections in recent times, the fact-checking agencies handled the same kind of misinformation that has attacked voting in the US. However, stopping fake content before it goes viral remains an intense challenge. This paper examines a sample database of the 2018 Brazilian election articles shared by Brazilians over social media platforms. We evaluated three different configuration of Long Short-Term Memory. Experiment results indicate that the 3-layer Deep BiLSTMs with trainable word embeddings configuration was the best structure for fake news detection. We noticed that the developments in deep learning could potentially benefit fake news research." @default.
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- W2981566181 date "2019-01-01" @default.
- W2981566181 modified "2023-10-01" @default.
- W2981566181 title "Brazilian Presidential Elections in the Era of Misinformation: A Machine Learning Approach to Analyse Fake News" @default.
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- W2981566181 doi "https://doi.org/10.1007/978-3-030-33904-3_7" @default.
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