论文标题
域级检测和虚假信息的破坏
Domain-Level Detection and Disruption of Disinformation
论文作者
论文摘要
在短短20年的时间里,我们是否从互联网的承诺中如何民主化知识的机会,使世界更加了解和开明,转变为当今互联网的每日恐怖片?我们陷入了由谎言,阴谋和普遍胡说八道组成的虚假信息,所有这些都具有现实世界中的影响,从可怕的人类权利侵犯人权到威胁我们的民主和全球公共卫生。尽管互联网很广泛,但虚假信息的小贩似乎更本地化。为此,我们描述了一个域级分析,用于预测域是否是分发或放大虚假信息的同谋。该过程分析了域之间的基本域内容和超链接连接性,以预测一个域是否在虚假信息中兜售。这些基本的见解扩展到对电报和Twitter上的虚假信息的分析。从这些见解中,我们提出,搜索引擎和社交媒体建议算法可以系统地发现和降低最坏的虚假犯罪者,从而将一些信任和理智归还给我们的在线社区。
How, in 20 short years, did we go from the promise of the internet to democratize access to knowledge and make the world more understanding and enlightened, to the litany of daily horrors that is today's internet? We are awash in disinformation consisting of lies, conspiracies, and general nonsense, all with real-world implications ranging from horrific humans rights violations to threats to our democracy and global public health. Although the internet is vast, the peddlers of disinformation appear to be more localized. To this end, we describe a domain-level analysis for predicting if a domain is complicit in distributing or amplifying disinformation. This process analyzes the underlying domain content and the hyperlinking connectivity between domains to predict if a domain is peddling in disinformation. These basic insights extend to an analysis of disinformation on Telegram and Twitter. From these insights, we propose that search engines and social-media recommendation algorithms can systematically discover and demote the worst disinformation offenders, returning some trust and sanity to our online communities.