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
{"title":"社会突发事件中的语言动态:新冠肺炎微博热词调查","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":"{\"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}","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

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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Glottometrics
Glottometrics LINGUISTICS-
CiteScore
0.50
自引率
0.00%
发文量
0
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.
期刊最新文献
The meaning distributions on different levels of granularity The journal SMIL - Statistical Methods in Linguistics (1962-1976) - some notes about the history of quantitative linguistics in Scandinavia and beyond A comparison of two text specificity measures analyzing a heterogenous text corpus Fellow or foe? A quantitative thematic exploration into Putin's and Trump's stylometric features Quantifying syntax similarity with a polynomial representation of dependency trees
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1