量化语言中主题波动的动态
Quantifying the dynamics of topical fluctuations in language
摘要：
大型历时语料库的出现为越来越多的语言演变和意义变化的定量研究提供了动力。本研究的中心量是语篇中语言元素的标记频率，频率的变化反映了元素的受欢迎程度或选择适合度。然而，语料库频率可能会因为各种各样的原因而改变，包括纯粹的随机抽样效应，或者因为语料库由当代媒体和小说文本组成，其中潜在的主题随着文化和社会政治趋势而起伏。在这项工作中，我们引入了一个简单的模型，用于控制语料库中的主题波动-主题文化平流模型-并演示了它如何提供一个强大的基线的变化，随着时间的推移，词频的变化。我们验证了跨越两个世纪的历时语料库的模型，和一个精心控制的人工语言变化的情况下，然后用它来纠正历史时间序列的主题波动。最后，我们使用该模型表明，新词的出现通常与热门话题的兴起相对应。这表明，一些词汇的创新发生由于不断增长的交际需要在一个子空间的词汇，和主题文化平流模型可以用来量化。
英文摘要：
The availability of large diachronic corpora has provided the impetus for a growing body of quantitative research on language evolution and meaning change. The central quantities in this research are token frequencies of linguistic elements in texts, with changes in frequency taken to reflect the popularity or selective fitness of an element. However, corpus frequencies may change for a wide variety of reasons, including purely random sampling effects, or because corpora are composed of contemporary media and fiction texts within which the underlying topics ebb and flow with cultural and socio-political trends. In this work, we introduce a simple model for controlling for topical fluctuations in corpora - the topical-cultural advection model - and demonstrate how it provides a robust baseline of variability in word frequency changes over time. We validate the model on a diachronic corpus spanning two centuries, and a carefully-controlled artificial language change scenario, and then use it to correct for topical fluctuations in historical time series. Finally, we use the model to show that the emergence of new words typically corresponds with the rise of a trending topic. This suggests that some lexical innovations occur due to growing communicative need in a subspace of the lexicon, and that the topical-cultural advection model can be used to quantify this.
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