Opinions on Homeopathy for COVID-19 on Twitter.

Jeevith Bopaiah, Kiran Garimella, Ramakanth Kavuluru
{"title":"Opinions on Homeopathy for COVID-19 on Twitter.","authors":"Jeevith Bopaiah, Kiran Garimella, Ramakanth Kavuluru","doi":"10.1145/3501247.3531575","DOIUrl":null,"url":null,"abstract":"<p><p>Homeopathy is a medical system originating in Germany more than 200 years ago. Based on prior investigations, mainstream health agencies and medical research communities indicate that there is little evidence that homeopathy can be an effective treatment for any specific health condition. However, it continues to be practiced as a popular form of alternative medicine in many countries, even during the ongoing COVID-19 pandemic. In this paper, we mine opinions on homeopathy for COVID-19 expressed in Twitter data. Our experiments are conducted with a dataset of nearly 60K tweets collected during a seven month period ending in July 2020. We first built text classifiers (linear and neural models) to mine opinions on homeopathy (positive, negative, neutral) from tweets using a dataset of 2400 hand-labeled tweets obtaining an average macro F-score of 81.5% for the positive and negative classes. We applied this model to identify opinions from the full dataset. Our results show that the number of unique positive tweets is twice that of the number of unique negative tweets; but when including retweets, there are 23% more negative tweets overall indicating that negative tweets are getting more retweets and better traction on Twitter. Using a word shift graph analysis on the Twitter bios of authors of positive and negative tweets, we observe that opinions on homeopathy appear to be correlated with political/religious ideologies of the authors (e.g., liberal vs nationalist, atheist vs Hindu). To our knowledge, this is the first study to analyze public opinions on homeopathy on any social media platform. Our results surface a tricky landscape for public health agencies as they promote evidence-based therapies and preventative measures for COVID-19.</p>","PeriodicalId":93136,"journal":{"name":"Proceedings of the ... ACM Web Science Conference. ACM Web Science Conference","volume":"2022 ","pages":"359-363"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9472594/pdf/nihms-1833661.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... ACM Web Science Conference. ACM Web Science Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3501247.3531575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/6/26 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Homeopathy is a medical system originating in Germany more than 200 years ago. Based on prior investigations, mainstream health agencies and medical research communities indicate that there is little evidence that homeopathy can be an effective treatment for any specific health condition. However, it continues to be practiced as a popular form of alternative medicine in many countries, even during the ongoing COVID-19 pandemic. In this paper, we mine opinions on homeopathy for COVID-19 expressed in Twitter data. Our experiments are conducted with a dataset of nearly 60K tweets collected during a seven month period ending in July 2020. We first built text classifiers (linear and neural models) to mine opinions on homeopathy (positive, negative, neutral) from tweets using a dataset of 2400 hand-labeled tweets obtaining an average macro F-score of 81.5% for the positive and negative classes. We applied this model to identify opinions from the full dataset. Our results show that the number of unique positive tweets is twice that of the number of unique negative tweets; but when including retweets, there are 23% more negative tweets overall indicating that negative tweets are getting more retweets and better traction on Twitter. Using a word shift graph analysis on the Twitter bios of authors of positive and negative tweets, we observe that opinions on homeopathy appear to be correlated with political/religious ideologies of the authors (e.g., liberal vs nationalist, atheist vs Hindu). To our knowledge, this is the first study to analyze public opinions on homeopathy on any social media platform. Our results surface a tricky landscape for public health agencies as they promote evidence-based therapies and preventative measures for COVID-19.

Twitter 上对 COVID-19 顺势疗法的看法。
顺势疗法是 200 多年前起源于德国的一种医疗体系。根据先前的调查,主流卫生机构和医学研究界指出,几乎没有证据表明顺势疗法可以有效治疗任何特定的健康问题。然而,即使在 COVID-19 大流行期间,顺势疗法作为一种流行的替代医学形式在许多国家仍在继续使用。在本文中,我们挖掘了 Twitter 数据中有关 COVID-19 顺势疗法的观点。我们使用截至 2020 年 7 月的 7 个月期间收集的近 6 万条推文数据集进行了实验。我们首先建立了文本分类器(线性模型和神经模型),利用 2400 个手工标记的推文数据集挖掘推文中关于顺势疗法的观点(正面、负面、中立),结果发现正面和负面类别的平均宏观 F 分数为 81.5%。我们将该模型用于识别全部数据集中的观点。我们的结果显示,独特的正面推文数量是独特的负面推文数量的两倍;但如果将转发计算在内,负面推文的总体数量要多出 23%,这表明负面推文在 Twitter 上获得了更多的转发和更好的关注度。通过对正面推文和负面推文作者的推特简历进行词移图分析,我们发现,对顺势疗法的看法似乎与作者的政治/宗教意识形态(如自由主义与民族主义、无神论者与印度教)相关。据我们所知,这是第一项分析公众在任何社交媒体平台上对顺势疗法的看法的研究。我们的研究结果表明,公共卫生机构在推广循证疗法和 COVID-19 预防措施时面临着棘手的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信