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Fusion-Based Multimodal Detection of Hoaxes in Social Networks

机译:基于融合的社交网络恶作剧多模式检测

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Social networks make it possible to share information rapidly and massively. Yet, one of their major drawback comes from the absence of verification of the piece of information, especially with viral messages. This is the issue addressed by the participants of the Verification Multimedia Use task of Mediaeval 2016. They used several approaches and clues from different modalities (text, image, social information). In this paper, we explore the interest of combining and merging these approaches in order to evaluate the predictive power of each modality and to make the most of their potential complementarity.
机译:社交网络使得可以快速和大规模地分享信息。然而,他们的一个主要缺点是没有验证这条信息,特别是有病毒信息。这是验证多媒体使用任务2016年验证多媒体使用任务的问题的问题。它们使用了不同模式的几种方法和线索(文本,图像,社交信息)。在本文中,我们探讨了组合和合并这些方法的兴趣,以评估每种方式的预测力,并充分利用它们的潜在互补性。

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