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通过识别 Twitter 话语中对疫苗信心的信念框架,扩大犹豫不决概况的发现规模。

Scaling up the discovery of hesitancy profiles by identifying the framing of beliefs towards vaccine confidence in Twitter discourse.

机构信息

Department of Computer Science, Human Language Technology Research Institute, University of Texas at Dallas, Richardson, TX, 75080, USA.

Department of Health Society and Behavior, Department of Pediatrics, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, Irvine, CA, 92617, USA.

出版信息

J Behav Med. 2023 Apr;46(1-2):253-275. doi: 10.1007/s10865-022-00328-z. Epub 2022 May 30.

Abstract

Our study focused on the discovery of how vaccine hesitancy is framed in Twitter discourse, allowing us to recognize at-scale all tweets that evoke any of the hesitancy framings as well as the stance of the tweet authors towards the frame. By categorizing the hesitancy framings that propagate misinformation, address issues of trust in vaccines, or highlight moral issues or civil rights, we were able to empirically recognize their ontological commitments. Ontological commitments of vaccine hesitancy framings couples with the stance of tweet authors allowed us to identify hesitancy profiles for two most controversial yet effective and underutilized vaccines for which there remains substantial reluctance among the public: the Human Papillomavirus and the COVID-19 vaccines. The discovered hesitancy profiles inform public health messaging approaches to effectively reach Twitter users with promise to shift or bolster vaccine attitudes.

摘要

我们的研究重点是发现疫苗犹豫在 Twitter 话语中是如何被构建的,这使我们能够大规模识别出所有引发任何犹豫框架的推文,以及推文作者对框架的立场。通过对传播错误信息、解决疫苗信任问题或突出道德问题或公民权利的犹豫框架进行分类,我们能够从经验上认识到它们的本体承诺。疫苗犹豫框架的本体承诺与推文作者的立场相结合,使我们能够为两种最具争议但有效且未充分利用的疫苗确定犹豫概况,这两种疫苗在公众中仍然存在很大的抵触情绪:人乳头瘤病毒和 COVID-19 疫苗。发现的犹豫概况为公共卫生信息传递方法提供了信息,以有效地接触到有希望改变或增强疫苗态度的 Twitter 用户。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba86/9148945/a1038589ebe0/10865_2022_328_Fig1_HTML.jpg

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