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Measuring the Impact of Readability Features in Fake News Detection.

, , , , , , and . LREC, page 1404-1413. European Language Resources Association, (2020)

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Linguistic Analysis Model for Monitoring User Reaction on Satirical News for Brazilian Portuguese., , , , , and . PROPOR, volume 12037 of Lecture Notes in Computer Science, page 313-320. Springer, (2020)Improving Opinion Summarization by Assessing Sentence Importance in On-line Reviews., , , and . STIL, page 32-36. Sociedade Brasileira de Computação, (2017)Experiments with CST-Based Multidocument Summarization., and . TextGraphs@ACL, page 74-82. Association for Computational Linguistics, (2010)HateBR: A Large Expert Annotated Corpus of Brazilian Instagram Comments for Offensive Language and Hate Speech Detection., , , , and . LREC, page 7174-7183. European Language Resources Association, (2022)NoHateBrazil: A Brazilian Portuguese Text Offensiveness Analysis System., , , , and . RANLP, page 1180-1186. INCOMA Ltd., Shoumen, Bulgaria, (2023)A base de dados lexical e a interface web do TeP 2.0: thesaurus eletrônico para o Português do Brasil., , , and . WebMedia (Companion), page 390-392. ACM, (2008)Contributions to the Study of Fake News in Portuguese: New Corpus and Automatic Detection Results., , , , , and . PROPOR, volume 11122 of Lecture Notes in Computer Science, page 324-334. Springer, (2018)Creating a Portuguese Context Sensitive Lexicon for Sentiment Analysis., , and . PROPOR, volume 11122 of Lecture Notes in Computer Science, page 335-344. Springer, (2018)Improving Content Selection for Update Summarization with Subtopic-Enriched Sentence Ranking Functions., and . Int. J. Comput. Linguistics Appl., 7 (2): 111-128 (2016)Factual or Biased? Predicting Sentence-Level Factuality and Bias of News., , , and . CoRR, (2023)