论文标题
多模式的错误信息检测：方法，挑战和机遇
Multi-modal Misinformation Detection: Approaches, Challenges and Opportunities
论文作者
论文摘要
随着社交媒体平台从基于文本的论坛演变为多模式环境，社交媒体中错误信息的性质也正在相应地发生。利用这样一个事实，即图像和视频等视觉方式对用户更有利，更具吸引力，并且有时会粗略地掠过文本内容，否则信息散布器最近针对模式之间的上下文连接，例如文本和图像。因此，许多研究人员开发了自动技术，用于检测基于Web的内容中可能的跨模式不一致。除了面临挑战和缺点之外，我们还分析，分类和确定现有方法，以便在多模式错误信息检测领域发掘新的研究机会。
As social media platforms are evolving from text-based forums into multi-modal environments, the nature of misinformation in social media is also transforming accordingly. Taking advantage of the fact that visual modalities such as images and videos are more favorable and attractive to the users and textual contents are sometimes skimmed carelessly, misinformation spreaders have recently targeted contextual connections between the modalities e.g., text and image. Hence many researchers have developed automatic techniques for detecting possible cross-modal discordance in web-based content. We analyze, categorize and identify existing approaches in addition to challenges and shortcomings they face in order to unearth new research opportunities in the field of multi-modal misinformation detection.
