{"title":"Dynamics of language in social emergency: investigating COVID-19 hot words on Weibo","authors":"Yi Zhou, Rui Li, Guangfeng Chen, Haitao Liu","doi":"10.53482/2022_52_395","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":51918,"journal":{"name":"Glottometrics","volume":null,"pages":null},"PeriodicalIF":0.2000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Glottometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53482/2022_52_395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"LINGUISTICS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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.