COVID-19大流行期间的在线医学话语:语义类别和态度

Irina Ovchinnikova, Liana Ermakova, Diana Nurbakova
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引用次数: 0

摘要

本文介绍了医学专业论坛出版物的语篇、语义和情感分析结果。门户网站MirVracha专业社区内的计算机媒介通信(CMC)揭示了医学专业话语的多样性特点,因为该门户网站包括非正式帖子和聊天以及官方和科学出版物。我们研究了MirVracha在2020年夏季至2021年冬季发表的材料(数据集包括超过50万字)。我们揭示了在线医学专业话语的主要语义类别,并在疫情和社会事件的背景下研究了出版物中讨论的主题的动态。COVID-19大流行期间在线医学专业话语的主要语义类别是诊断和研究类别。基于话语分析的结果,我们描述了门户网站用户的兴趣和态度,以及他们在专业社区中用来表达他们态度的语言手段。医学专业人员主要对研究材料和结果感兴趣。基于情感分析,我们揭示了在出版物中揭示的态度。医学专业CMC对话题的态度主要是中立的。在帖子和个人叙述中,门户用户在与语义诊断和官僚主义类别相关的帖子中讨论政治语境并表达消极态度。©2022别尔哥罗德国立国立研究大学。版权所有。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online medical discourse during the COVID-19 pandemic: semantic categories and attitudes
The paper presents the results of the discourse, semantic and sentiment analysis of the medical professional forum publications. Computer-mediated communication (CMC) within the professional community on the portal MirVracha reveals a diversity of peculiarities of medical professional discourse since the portal includes informal posts and chats alongside official and scientific publications. We study materials of MirVracha published in summer 2020 – winter 2021 (dataset includes more than 0.5 million words). We reveal dominant semantic categories of online medical professional discourse and examine the dynamic of topics discussed in the publications against the backdrop of the pandemic situation and social events. The dominant semantic categories of online medical professional discourse during the COVID-19 pandemic are the Diagnosis and Research categories. Based on the results of discourse analysis, we describe the interests and attitudes of the portal users and linguistic means they use to verbalize their attitudes within the professional community. The medical professionals are primarily interested in research materials and outcomes. Based on sentiment analysis, we uncover attitudes revealed in the publications. Medical professional CMC shows mainly neutral attitudes to the topics. In the posts and personal narratives, the portal users discuss political context and express the negative attitude in posts associated with semantic Diagnosis and Bureaucracy categories. © 2022 Belgorod State National Research University. All rights reserved.
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