In the past decade, the social networks platforms and micro-blogging sites such as Facebook, Twitter, Instagram, and Weibo have become an integral part of our day-to-day activities and is widely used all over the world by billions of users to share their views and circulate information in the form of messages, pictures, and videos. These are even used by government agencies to spread important information through their verified Facebook accounts and official Twitter handles, as they can reach a huge population within a limited time window. However, many deceptive activities like propaganda and rumor can mislead users on a daily basis. In these COVID times, fake news and rumors are very prevalent and are shared in a huge number which has created chaos in this tough time. And hence, the need for Fake News Detection in the present scenario is inevitable. In this paper, we survey the recent literature about different approaches to detect fake news over the Internet. In particular, we firstly discuss fake news and the various terms related to it that have been considered in the literature. Secondly, we highlight the various publicly available datasets and various online tools that are available and can debunk Fake News in real-time. Thirdly, we describe fake news detection methods based on two broader areas i.e., its content and the social context. Finally, we provide a comparison of various techniques that are used to debunk fake news.
翻译:过去十年来,社交网络平台和微博客网站,如Facebook、Twitter、Instagram、Instagram和Weibo等,已经成为我们日常活动的一个组成部分,被世界各地数十亿用户广泛使用,以信息、图片和视频的形式分享观点和传播信息。甚至政府机构还利用这些平台和微博网站,通过经核实的Facebook账户和官方推特手柄传播重要信息,因为它们可以在有限的时间窗口内接触到大量人口。然而,宣传和谣言等许多欺骗性活动每天都会误导用户。在这些COVID时代,假消息和谣言非常普遍,而且被大量用户分享,在这个艰难时期造成了混乱。因此,在目前情况下,对假新闻探测的必要性是不可避免的。在本文中,我们调查最近关于通过不同方法在互联网上探测假新闻的文献。特别是,我们首先讨论假新闻和文献中考虑的各种术语。第二,我们强调各种公开可用的数据集和各种在线工具,在COVID时代非常普遍,而且可以分享大量新闻和分享,因此在这个艰难时期造成了混乱。因此,在目前情况下,我们不可避免地需要假新闻探测假新闻。我们使用两种方法,最后用各种方法,我们用来对各种新闻进行虚假的比较。