A Sentiment-Based Multimodal Method to Detect Fake News

Igor Maffei Libonati Maia, M. Souza, Flávio Roberto Matias da Silva, Paulo Márcio Souza Freire, R. Goldschmidt
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引用次数: 5

Abstract

The dissemination of news through digital media has amplified Fake News proliferation. In the face of this scenario, sentiment-based methods have presented promising results in Fake News detection. Although sentiment-based methods can extract sentiment (i.e., polarity and/or emotion) from either texts or images available in news, the ones applied to Portuguese-written news have considered sentiment exclusively extracted from texts. Thus, this study proposes a multimodal method that, besides the polarity and emotions extracted from texts, also considers sentiment extracted from news' images in order to detect Fake News written in Portuguese. The proposed method showed promising results in experimental data, overcoming the baseline methods in 8 p.p.
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基于情感的多模态假新闻检测方法
通过数字媒体传播新闻加剧了假新闻的泛滥。面对这种情况,基于情绪的方法在假新闻检测中表现出了令人鼓舞的结果。虽然基于情感的方法可以从新闻中可用的文本或图像中提取情感(即极性和/或情感),但应用于葡萄牙语书面新闻的方法只考虑从文本中提取的情感。因此,本研究提出了一种多模态方法,除了从文本中提取极性和情感外,还考虑了从新闻图像中提取的情感,以检测葡萄牙语写的假新闻。该方法在实验数据中取得了令人满意的结果,克服了8pp的基线方法。
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