Papers by Roney Santos

2 papers
Measuring the Impact of Readability Features in Fake News Detection (2020.lrec-1)

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Challenge: Recent efforts to detect fake news use language-based approaches to detect news articles . authors show that readability features can improve classification accuracy .
Approach: They propose to use readability features to detect fake news in the Brazilian Portuguese language . they show that such features can achieve up to 92% classification accuracy .
Outcome: The proposed features achieve up to 92% accuracy and may improve previous classification results.
Puntuguese: A Corpus of Puns in Portuguese with Micro-edits (2024.lrec-main)

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Challenge: Existing corpus of punning humor in Portuguese is unfit for machine learning due to data leakage.
Approach: They propose to use Puntuguese to create a corpus of punning humor in Portuguese that is significantly more difficult to recognize than the previous corpus.
Outcome: The proposed corpus achieves an F1-Score of 68.9% and is significantly more difficult than the previous corpus.

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