Department of Chinese Language and Literature, Peking University, Beijing, China.
Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong, China.
PLoS One. 2021 Feb 3;16(2):e0245984. doi: 10.1371/journal.pone.0245984. eCollection 2021.
This paper adopts models from epidemiology to account for the development and decline of neologisms based on internet usage. The research design focuses on the issue of whether a host-driven epidemic model is well-suited to explain human behavior regarding neologisms. We extracted the search frequency data from Google Trends that covers the ninety most influential Chinese neologisms from 2008-2016 and found that the majority of them possess a similar rapidly rising-decaying pattern. The epidemic model is utilized to fit the evolution of these internet-based neologisms. The epidemic model not only has good fitting performance to model the pattern of rapid growth, but also is able to predict the peak point in the neologism's life cycle. This result underlines the role of human agents in the life cycle of neologisms and supports the macro-theory that the evolution of human languages mirrors the biological evolution of human beings.
本文采用流行病学模型，根据互联网使用情况来解释新词的发展和衰落。研究设计侧重于宿主驱动的传染病模型是否适合解释人类对新词的行为。我们从谷歌趋势中提取了搜索频率数据，其中包括 2008 年至 2016 年 90 个最有影响力的中文新词，发现它们中的大多数都具有相似的快速上升-下降模式。我们利用传染病模型来拟合这些基于互联网的新词的演变。传染病模型不仅具有很好的拟合性能来模拟快速增长的模式，而且还能够预测新词生命周期中的峰值点。这一结果强调了人类主体在新词生命周期中的作用，并支持了人类语言的进化反映了人类生物进化的宏观理论。
