As social media platforms evolve 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 users, and textual content is 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 the challenges and shortcomings they face in order to unearth new research opportunities in the field of multi-modal misinformation detection.

中文翻译：

---

多模态错误信息检测：方法、挑战和机遇


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在发生相应变化。利用图像和视频等视觉模式对用户更有利和更有吸引力，以及文本内容有时会被粗心浏览的事实，错误信息传播者最近将目标对准了这些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来检测基于 Web 的内容中可能的跨模态不一致。除了它们面临的挑战和缺点外，我们还分析、分类和识别现有方法，以便在多模态错误信息检测领域发掘新的研究机会。