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Detecting the Evolution of Semantics and Individual Beliefs Through Statistical Analysis of Language Use

机译:通过语言使用的统计分析来检测语义和个人信仰的演变

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Individual differences in semantics and beliefs have up to now been identified primarily by questioning people. However, semantics and beliefs can also be observed in concrete, quantifiable contexts such as reaction-time experiments. Here we demonstrate an automatic mechanism which can replicate such semantics by observing regularities in language use through statistical text analysis. We postulate that human children, who are fantastic pattern recognizers, may also exploit this same information, thus our mechanism may be an essential module in a human-like cognitive system. In this article we first review the underlying theories and existing results, then present the tool itself. We validate the tool against existing semantic priming reaction-time results. Finally we use the tool to explore the evolution of beliefs extracted from three sources: the Bible, the works of Shakespeare and the contemporary British National Corpus.
机译:目前,语义和信仰的个人差异主要是通过质疑人们来识别的。然而,在混凝土中也可以观察到语义和信念,例如反应时间实验。在这里,我们展示了一种自动机制,可以通过通过统计文本分析观察语言使用的规律来复制此类语义。我们假设人类的儿童是奇妙的模式识别者,也可能利用相同的信息,因此我们的机制可能是人类认知系统中的重要模块。在本文中,我们首先审查潜在的理论和现有结果,然后介绍工具本身。我们验证了对现有语义启动反应时间结果的工具。最后,我们使用该工具来探索从三个来源提取的信仰的演变:圣经,莎士比亚和当代英国国家语料库的作品。

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