疫苗接种竞争社区的社会语言变异特征
Characterizing Sociolinguistic Variation in the Competing Vaccination Communities
摘要：
公共卫生从业者和政策制定者努力应对设计有效的基于信息的干预措施的挑战，以揭穿网络社区中的公共卫生错误信息。信息的“框架化”和“个性化”是设计有说服力的信息策略的关键特征之一。为了有效的健康传播，必须注重“基于偏好的框架”，其中考虑到目标亚社区的偏好。为了实现这一目标，重要的是要了解并因此根据其社会互动来描述目标亚社区的特征。在与健康有关的错误信息的背景下，疫苗接种仍然是最普遍的不和谐话题。因此，在本文中，我们对Twitter上两个相互竞争的疫苗接种社区进行了社会语言学分析：“亲疫苗接种者”或相信疫苗接种有效性的个人，以及“反疫苗接种者”或反对疫苗接种的个人。我们的数据分析表明，两个社区之间的语言差异显着的语言强化，代词和不确定词的使用。我们的网络水平的分析表明，两个社区之间的网络密度，回声室，和EI指数的显着差异。我们假设，这些社会语言学的差异可以被用来作为代理的特点和理解这些社区，以设计更好的信息干预。
英文摘要：
Public health practitioners and policy makers grapple with the challenge of devising effective message-based interventions for debunking public health misinformation in cyber communities. "Framing" and "personalization" of the message is one of the key features for devising a persuasive messaging strategy. For an effective health communication, it is imperative to focus on "preference-based framing" where the preferences of the target sub-community are taken into consideration. To achieve that, it is important to understand and hence characterize the target sub-communities in terms of their social interactions. In the context of health-related misinformation, vaccination remains to be the most prevalent topic of discord. Hence, in this paper, we conduct a sociolinguistic analysis of the two competing vaccination communities on Twitter: "pro-vaxxers" or individuals who believe in the effectiveness of vaccinations, and "anti-vaxxers" or individuals who are opposed to vaccinations. Our data analysis show significant linguistic variation between the two communities in terms of their usage of linguistic intensifiers, pronouns, and uncertainty words. Our network-level analysis show significant differences between the two communities in terms of their network density, echo-chamberness, and the EI index. We hypothesize that these sociolinguistic differences can be used as proxies to characterize and understand these communities to devise better message interventions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
