社会突发事件中的语言动态:新冠肺炎微博热词调查

IF 0.2 Q4 LINGUISTICS

Glottometrics Pub Date : 2022-01-01 DOI:10.53482/2022_52_395

Yi Zhou, Rui Li, Guangfeng Chen, Haitao Liu

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引用次数: 0

摘要

本研究利用词嵌入技术，跟踪新冠疫情期间新浪微博热词的频率和语义变化，探讨危机期间语言和话语的变化。更具体地说，在词频等级、流行病数据和词义变化率之间进行了相关检验。结果表明，部分热词的出现频率随大流行数据和其他热词出现频率的变化而变化，其中与美国大流行数据的相关性显著，与中国大流行数据的相关性不显著。此外，2020年2月出现了最明显的语义变化，其中大部分是WAR隐喻的近邻。新冠肺炎相关热词的频率变化与最近邻居之间的相关性表现出一些可接受的特殊性。本研究通过观察社交媒体内涵层面的微小语义变化，证明了通过语言变化研究话语的有效性，为新冠肺炎疫情的影响增加了新的视角。

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Dynamics of language in social emergency: investigating COVID-19 hot words on Weibo

Drawing on word embeddings techniques and tracking the frequency and semantic change of hot words on Sina Weibo during the COVID-19 pandemic, this study investigates how language and discourse change during crisis. More specifically, correlation tests were conducted between word frequency ranks, pandemic data, and word meaning change ratio. Results indicated that the frequency of some hot words changed with both pandemic data and the frequency of other hot words, which were significantly correlated with the American pandemic data rather than that of China. Moreover, February of 2020 saw the most distinctive semantic changes marked by a large part of the nearest neighbors for WAR metaphors. The correlations between changes in the frequency and nearest neighbors of COVID-19 related hot words exhibited some acceptable peculiarities. This study proves the availability of studying discourse through language change by observing minor semantic change on connotation level from social media, which adds a new perspective to the impact of the COVID-19 pandemic.

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来源期刊

Glottometrics LINGUISTICS-

CiteScore

0.50

自引率

0.00%

发文量

期刊介绍： The aim of Glottometrics is quantification, measurement and mathematical modeling of any kind of language phenomena. We invite contributions on probabilistic or other mathematical models (e.g. graph theoretic or optimization approaches) which enable to establish language laws that can be validated by testing statistical hypotheses.