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- W4293657499 abstract "During the COVID-19 pandemic, the misinformation problem arose again through social networks, like a harmful health advice and false solutions epidemic. In Brazil, one of the primary sources of misinformation is the messaging application WhatsApp. Thus, the automatic misinformation detection (MID) about COVID-19 in Brazilian Portuguese WhatsApp messages becomes a crucial challenge. Recently, some works presented different MID approaches for this purpose. Despite this success, most explored MID models remain complex black boxes. So, their internal logic and inner workings are hidden from users, which cannot fully understand why a MID model assessed a particular WhatsApp message as misinformation or not. Thus, in this article, we explore a post-hoc interpretability method called LIME to explain the predictions of MID approaches. Besides, we apply a textual analysis tool called LIWC to analyze WhatsApp messages’ linguistic characteristics and identify psychological aspects present in misinformation and non-misinformation messages. The results indicate that it is feasible to understand relevant aspects of the MID model’s predictions and find patterns on WhatsApp messages about COVID19. So, we hope that these findings help to understand the misinformation phenomena about COVID-19 in WhatsApp messages ." @default.
- W4293657499 created "2022-08-31" @default.
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- W4293657499 date "2022-01-01" @default.
- W4293657499 modified "2023-10-01" @default.
- W4293657499 title "Understanding Misinformation About COVID-19 in WhatsApp Messages" @default.
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- W4293657499 doi "https://doi.org/10.1007/978-3-031-15743-1_2" @default.
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