文本挖掘对气候变化的态度:推特语料库的情感分析

IF 1.9 4区 地球科学 Q3 ENVIRONMENTAL STUDIES Weather Climate and Society Pub Date : 2023-02-22 DOI:10.1175/wcas-d-22-0123.1
Zhewei Mi, Hongwei Zhan
{"title":"文本挖掘对气候变化的态度:推特语料库的情感分析","authors":"Zhewei Mi, Hongwei Zhan","doi":"10.1175/wcas-d-22-0123.1","DOIUrl":null,"url":null,"abstract":"\nMedia such as Twitter has become a platform for contemporary Americans to express their opinions and allow for reaction to public opinion. Climate change is a topic of ongoing social concern. Machine-automated processing facilitates big data analysis and is suitable for analyzing a large corpus of tweets. This paper uses R tools to conduct sentiment calculation and emotion analysis on the tweet corpus from 2015 to 2018 to present the overall tendency of citizens’ attitudes toward climate change topics. The keyword analysis finds that people focus on the message’s source; CLIMATE CHANGE and GLOBAL WARMING make an association. Supporters express FEAR and SURPRISE about extreme weather and opponents’ behavior, while opponents show ANGER, DISGUST and SADNESS about politicians manufacturing climate change stories about which they have no real feelings. This study also reveals that the automatic annotation tools are still inadequate, with limited emotion lexicon and identification of negation and sarcasm.","PeriodicalId":48971,"journal":{"name":"Weather Climate and Society","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Text mining attitudes towards climate change: Emotion and sentiment analysis of the Twitter corpus\",\"authors\":\"Zhewei Mi, Hongwei Zhan\",\"doi\":\"10.1175/wcas-d-22-0123.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nMedia such as Twitter has become a platform for contemporary Americans to express their opinions and allow for reaction to public opinion. Climate change is a topic of ongoing social concern. Machine-automated processing facilitates big data analysis and is suitable for analyzing a large corpus of tweets. This paper uses R tools to conduct sentiment calculation and emotion analysis on the tweet corpus from 2015 to 2018 to present the overall tendency of citizens’ attitudes toward climate change topics. The keyword analysis finds that people focus on the message’s source; CLIMATE CHANGE and GLOBAL WARMING make an association. Supporters express FEAR and SURPRISE about extreme weather and opponents’ behavior, while opponents show ANGER, DISGUST and SADNESS about politicians manufacturing climate change stories about which they have no real feelings. This study also reveals that the automatic annotation tools are still inadequate, with limited emotion lexicon and identification of negation and sarcasm.\",\"PeriodicalId\":48971,\"journal\":{\"name\":\"Weather Climate and Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Weather Climate and Society\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1175/wcas-d-22-0123.1\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Weather Climate and Society","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/wcas-d-22-0123.1","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0

摘要

推特等媒体已成为当代美国人表达意见和对公众舆论做出反应的平台。气候变化是一个社会持续关注的话题。机器自动化处理有助于大数据分析,适用于分析大型推文语料库。本文使用R工具对2015年至2018年的推特语料库进行情绪计算和情绪分析,以呈现公民对气候变化话题态度的总体趋势。关键词分析发现,人们关注信息的来源;气候变化和全球变暖形成了关联。支持者对极端天气和反对者的行为表示恐惧和惊讶,而反对者则对政客制造他们没有真实感受的气候变化故事表示愤怒、厌恶和悲伤。本研究还表明,自动注释工具仍然不足,情感词汇有限,否定和讽刺的识别能力有限。
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
Text mining attitudes towards climate change: Emotion and sentiment analysis of the Twitter corpus
Media such as Twitter has become a platform for contemporary Americans to express their opinions and allow for reaction to public opinion. Climate change is a topic of ongoing social concern. Machine-automated processing facilitates big data analysis and is suitable for analyzing a large corpus of tweets. This paper uses R tools to conduct sentiment calculation and emotion analysis on the tweet corpus from 2015 to 2018 to present the overall tendency of citizens’ attitudes toward climate change topics. The keyword analysis finds that people focus on the message’s source; CLIMATE CHANGE and GLOBAL WARMING make an association. Supporters express FEAR and SURPRISE about extreme weather and opponents’ behavior, while opponents show ANGER, DISGUST and SADNESS about politicians manufacturing climate change stories about which they have no real feelings. This study also reveals that the automatic annotation tools are still inadequate, with limited emotion lexicon and identification of negation and sarcasm.
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
Weather Climate and Society
Weather Climate and Society METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
3.40
自引率
13.60%
发文量
95
审稿时长
>12 weeks
期刊介绍: Weather, Climate, and Society (WCAS) publishes research that encompasses economics, policy analysis, political science, history, and institutional, social, and behavioral scholarship relating to weather and climate, including climate change. Contributions must include original social science research, evidence-based analysis, and relevance to the interactions of weather and climate with society.
期刊最新文献
On the risk efficiency of a weather index insurance product for the Brazilian semi-arid region Climate Change Driving Salinity an Overview of Vulnerabilities, Adaptations, and Challenges for Indonesian Agriculture Flash drought typologies and societal impacts: a worldwide review of occurrence, nomenclature, and experiences of local populations Transformative ecological and human impacts from climate change and diminished sea ice in the northern Bering Sea Future Heavy rainfall and flood risks for Native America under climate and demographic changes: A case study in Oklahoma
×
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