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Identifying propaganda in global social media

机译:识别全球社交媒体中的宣传

摘要

Disclosed is a scalable method for automatically deriving the topics discussed most prevalently in unstructured, multilingual text, and simultaneously revealing which topics are more biased towards one or another ‘information space’. The concept of the ‘information space’ is derived from Russian strategic doctrine on information warfare; an example of an ‘information space’ would be the portion of social media in which the Russian language is used. The disclosed method leverages this concept, in conjunction with unsupervised multilingual machine learning, to determine, automatically and without any built-in bias or preconceived notions of what is important, which topics are more discussed, for example, in one language than another. An analyst's attention can then be focused on the most important differences between national discourses, and insight more quickly gained into the areas (both topics and geographic regions) in which propaganda of the sort envisaged in Russian strategic doctrine may be taking hold.
机译:公开的是一种可扩展的方法,用于自动派生非结构化,多语言文本中最普遍讨论的主题,同时揭示哪些主题更偏向一个或另一个“信息空间”。 “信息空间”的概念源自俄罗斯关于信息战的战略学说; “信息空间”的一个示例是社交媒体中使用俄语的部分。所公开的方法利用该概念,结合无监督的多语言机器学习,来自动确定并且没有任何重要的内在偏见或先入为主的概念,例如,用一种语言而不是另一种语言来讨论哪些主题。然后,分析师的注意力可以集中在国家话语之间最重要的差异上,并更快地洞悉俄罗斯战略学说所设想的那种宣传领域(话题和地理区域)。

著录项

  • 公开/公告号US2018285342A1

    专利类型

  • 公开/公告日2018-10-04

    原文格式PDF

  • 申请/专利权人 PETER ALEXANDER CHEW;

    申请/专利号US201715472697

  • 发明设计人 PETER ALEXANDER CHEW;

    申请日2017-03-29

  • 分类号G06F17/27;G06F17/30;

  • 国家 US

  • 入库时间 2022-08-21 12:56:48

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