Abstract
This paper investigates the emergence of COVID-19 neologisms. It focuses on the strategies used to coin emerging neologisms, the relationship between the strategies and the usage preferences, as well as the correlation between internet usage data and epidemiological data. The internet usage data were collected from December 2019 to June 2020 from the Baidu Index, covering the usage of all five categories of the COVID-19 name variants. The epidemiological data, from the Chinese Center for Disease Control and Prevention, are statistics of newly confirmed cases, newly suspected cases, new deaths, and currently suspected cases at a given time. The study identified three strategies in the coinage of neologisms: categorization, avoidance, and synthesis. In addition, a strong correlation between emergent neologisms and pandemic developments was discovered with a binomial model, and the emerging neologisms demonstrated a skewed S-curve life cycle, which is different from the established S-curve model of replacement changes. In sum, by leveraging internet usage data, this first study of the life cycle of emergent neologisms has several contributions: A theory of how new words emerge, the correlation between emergent neologisms and emerging events, and the potential of modeling language use for epidemiological predictions.
Published Version
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