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<article article-type="research-article" dtd-version="1.2" xml:lang="ru" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><front><journal-meta><journal-id journal-id-type="issn">2313-8912</journal-id><journal-title-group><journal-title>Research Result. Theoretical and Applied Linguistics</journal-title></journal-title-group><issn pub-type="epub">2313-8912</issn></journal-meta><article-meta><article-id pub-id-type="doi">10.18413/2313-8912-2022-8-1-0-4</article-id><article-id pub-id-type="publisher-id">2710</article-id><article-categories><subj-group subj-group-type="heading"><subject>THEORY OF LANGUAGE</subject></subj-group></article-categories><title-group><article-title>&lt;strong&gt;Online medical discourse during the COVID-19 pandemic: semantic categories and attitudes&lt;/strong&gt;</article-title><trans-title-group xml:lang="en"><trans-title>&lt;strong&gt;Online medical discourse during the COVID-19 pandemic: semantic categories and attitudes&lt;/strong&gt;</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Ovchinnikova</surname><given-names>Irina G.</given-names></name><name xml:lang="en"><surname>Ovchinnikova</surname><given-names>Irina G.</given-names></name></name-alternatives><email>ovchinnikova.ig@1msmu.ru</email><xref ref-type="aff" rid="aff1" /></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Ermakova</surname><given-names>Liana M.</given-names></name><name xml:lang="en"><surname>Ermakova</surname><given-names>Liana M.</given-names></name></name-alternatives><email>liana.ermakova@univ-brest.fr</email><xref ref-type="aff" rid="aff2" /></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Nurbakova</surname><given-names>Diana M.</given-names></name><name xml:lang="en"><surname>Nurbakova</surname><given-names>Diana M.</given-names></name></name-alternatives><email>diana.nurbakova@insa-lyon.fr</email><xref ref-type="aff" rid="aff3" /></contrib></contrib-group><aff id="aff1"><institution>Sechenov First Moscow State Medical University, Russia</institution></aff><aff id="aff3"><institution>National Institute of Applied Sciences of Lyon (INSA Lyon), France</institution></aff><aff id="aff2"><institution>The University of Western Brittany, France</institution></aff><pub-date pub-type="epub"><year>2022</year></pub-date><volume>8</volume><issue>1</issue><fpage>0</fpage><lpage>0</lpage><self-uri content-type="pdf" xlink:href="/media/linguistics/2022/1/Лингвистика_57-78.pdf" /><abstract xml:lang="ru"><p>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 &amp;ndash; 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.</p></abstract><trans-abstract xml:lang="en"><p>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 &amp;ndash; 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.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>Online Medical Discourse</kwd><kwd>COVID-19</kwd><kwd>Doctor-Doctor Communication</kwd><kwd>Discursive Category</kwd><kwd>Sentiment Analyses</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Online Medical Discourse</kwd><kwd>COVID-19</kwd><kwd>Doctor-Doctor Communication</kwd><kwd>Discursive Category</kwd><kwd>Sentiment Analyses</kwd></kwd-group></article-meta></front><back><ref-list><title>Список литературы</title><ref id="B1"><mixed-citation>Abd-Alrazaq, A., Alhuwail, D., Househ, M., Hamdi, M. and Shah, Z. (2020). 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