In recent years, rumors have had a devastating impact on society, making rumor detection a significant challenge. However, the studies on rumor detection ignore the intense emotions of images in the rumor content. This paper verifies that the image emotion improves the rumor detection efficiency. A Multimodal Dual Emotion feature in rumor detection, which consists of visual and textual emotions, is proposed. To the best of our knowledge, this is the first study which uses visual emotion in rumor detection. The experiments on real datasets verify that the proposed features outperform the state-of-the-art sentiment features, and can be extended in rumor detectors while improving their performance.

翻译：近些年来,谣言对社会产生了毁灭性影响,使谣言探测成为一项重大挑战。然而,关于谣言检测的研究忽略了谣言内容中图像的强烈情绪。 本文证实,图像情感提高了谣言检测的效率。 提出了由视觉和文字情感组成的谣言检测中的多模式双重情感特征。 据我们所知,这是首项利用视觉情感探测谣言的研究。 真实数据集的实验证实,所推荐的特征超过了最先进的情绪特征,可以在改善其性能的同时,在谣言探测器中加以扩展。