Social media has become a popular means for people to consume and share the news. At the same time, however, it has also enabled the wide dissemination of fake news, that is, news with intentionally false information, causing significant negative effects on society. To mitigate this problem, the research of fake news detection has recently received a lot of attention. Despite several existing computational solutions on the detection of fake news, the lack of comprehensive and community-driven fake news data sets has become one of major roadblocks. Not only existing data sets are scarce, they do not contain a myriad of features often required in the study such as news content, social context, and spatiotemporal information. Therefore, in this article, to facilitate fake news-related research, we present a fake news data repository FakeNewsNet, which contains two comprehensive data sets with diverse features in news content, social context, and spatiotemporal information. We present a comprehensive description of the FakeNewsNet, demonstrate an exploratory analysis of two data sets from different perspectives, and discuss the benefits of the FakeNewsNet for potential applications on fake news study on social media.

中文翻译：

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FakeNewsNet：一个具有新闻内容，社交环境和时空信息的数据存储库，用于研究社交媒体上的虚假新闻。

社交媒体已成为人们消费和分享新闻的一种流行手段。但是，与此同时，它也使得伪造新闻，即带有故意虚假信息的新闻的广泛传播，对社会产生了重大的负面影响。为了缓解这个问题，最近对假新闻检测的研究引起了广泛的关注。尽管存在几种检测假新闻的计算解决方案，但缺乏全面的，社区驱动的假新闻数据集已成为主要障碍之一。不仅现有数据集稀缺，而且它们不包含研究中经常需要的许多功能，例如新闻内容，社会背景和时空信息。因此，在本文中，为了促进与虚假新闻相关的研究，我们提出了一个虚假新闻数据存储库FakeNewsNet，其中包含两个全面的数据集，这些新闻集在新闻内容，社交环境和时空信息方面具有不同的功能。我们将对FakeNewsNet进行全面描述，展示从不同角度对两个数据集的探索性分析，并讨论FakeNewsNet在社交媒体上假新闻研究中潜在应用的好处。