In the past few years, the research community has dedicated growing interest to the issue of false news circulating on social networks. The widespread attention on detecting and characterizing deceptive information has been motivated by considerable political and social backlashes in the real world. As a matter of fact, social media platforms exhibit peculiar characteristics, with respect to traditional news outlets, which have been particularly favorable to the proliferation of false news. They also present unique challenges for all kind of potential interventions on the subject. As this issue becomes of global concern, it is also gaining more attention in academia. The aim of this survey is to offer a comprehensive study on the recent advances in terms of detection, characterization and mitigation of false news that propagate on social media, as well as the challenges and the open questions that await future research on the field. We use a data-driven approach, focusing on a classification of the features that are used in each study to characterize false information and on the datasets used for instructing classification methods. At the end of the survey, we highlight emerging approaches that look most promising for addressing false news.

中文翻译：

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社交媒体上的虚假新闻

在过去的几年里，研究界对社交网络上流传的虚假新闻问题的兴趣日益浓厚。对检测和表征欺骗性信息的广泛关注是由现实世界中相当大的政治和社会反弹推动的。事实上，相对于传统新闻媒体，社交媒体平台表现出独特的特征，尤其有利于虚假新闻的泛滥。它们还为有关该主题的各种潜在干预措施提出了独特的挑战。随着这个问题成为全球关注的焦点，它也越来越受到学术界的关注。本次调查的目的是对社交媒体上传播的虚假新闻的检测、表征和缓解方面的最新进展进行全面研究，以及等待该领域未来研究的挑战和未解决的问题。我们使用数据驱动的方法，专注于对每项研究中用于表征虚假信息的特征和用于指导分类方法的数据集进行分类。在调查结束时，我们重点介绍了最有希望解决虚假新闻的新兴方法。