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 METEOROLOGY & ATMOSPHERIC SCIENCES-

CiteScore

3.40

自引率

13.60%

发文量

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.