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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Russian Journal of Linguistics</journal-id><journal-title-group><journal-title xml:lang="en">Russian Journal of Linguistics</journal-title><trans-title-group xml:lang="ru"><trans-title>Russian Journal of Linguistics</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2687-0088</issn><issn publication-format="electronic">2686-8024</issn><publisher><publisher-name xml:lang="en">Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">26000</article-id><article-id pub-id-type="doi">10.22363/2687-0088-2021-25-1-105-124</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>Articles</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Статьи</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="zh"><subject>Articles</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Implicit vs explicit evaluation: How English-speaking Twitter users discuss migration problems</article-title><trans-title-group xml:lang="ru"><trans-title>Имплицитная vs эксплицитная оценка: как англоязычные пользователи Twitter обсуждают проблемы миграции</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Gabrielova</surname><given-names>Elena V.</given-names></name><name xml:lang="ru"><surname>Габриелова</surname><given-names>Елена Валерьевна</given-names></name></name-alternatives><bio xml:lang="en"><p>Ph.D., Senior Lecturer at the School of Foreign Languages at the National Research University “Higher School of Economics”. Her research interests include applied linguistics, political and mass communication, personal evaluation and emotions in Internet discourse, as well as political communication.</p></bio><bio xml:lang="ru"><p>кандидат филологических наук, старший преподаватель Школы иностранных языков Национального исследовательского университета «Высшая школа экономики». Сфера ее научных интересов включает языкознание, прикладную лингвистику, политическую коммуникацию, массовую коммуникацию, интернет-дискурс, оценочные суждения и эмотивность в интернет-дискурсе.</p></bio><email>evgabrielova@hse.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Maksimenko</surname><given-names>Olga I.</given-names></name><name xml:lang="ru"><surname>Максименко</surname><given-names>Ольга Ивановна</given-names></name></name-alternatives><bio xml:lang="en"><p>Dr. habil., Professor at the Faculty of Linguistics at Moscow Region State University. Her research interests embrace applied linguistics, quantitative linguistics, linguoconflictology, diplomatic discourse and sentiment analysis.</p></bio><bio xml:lang="ru"><p>доктор филологических наук, профессор кафедры теоретической и прикладной лингвистики Московского государственного областного университета. Сфера ее научных интересов включает языкознание, прикладную лингвистику, квантитативную лингвистику, лингвоконфликтологию, дипломатический дискурс, лингвистическую теорию эмоций, сентимент-анализ.</p></bio><email>maxbel7@yandex.ru</email><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">National Research University Higher School of Economics</institution></aff><aff><institution xml:lang="ru">Национальный исследовательский университет «Высшая школа экономики» (ВШЭ)</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Moscow Region State University</institution></aff><aff><institution xml:lang="ru">Московский государственный областной университет (МГОУ)</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2021-03-22" publication-format="electronic"><day>22</day><month>03</month><year>2021</year></pub-date><volume>25</volume><issue>1</issue><issue-title xml:lang="en">VOL 25, NO1 (2021)</issue-title><issue-title xml:lang="ru">ТОМ 25, №1 (2021)</issue-title><fpage>105</fpage><lpage>124</lpage><history><date date-type="received" iso-8601-date="2021-03-22"><day>22</day><month>03</month><year>2021</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2021, Gabrielova E.V., Maksimenko O.I.</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2021, Габриелова Е.В., Максименко О.И.</copyright-statement><copyright-statement xml:lang="zh">Copyright ©; 2021, Gabrielova E., Maksimenko O.</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="en">Gabrielova E.V., Maksimenko O.I.</copyright-holder><copyright-holder xml:lang="ru">Габриелова Е.В., Максименко О.И.</copyright-holder><copyright-holder xml:lang="zh">Gabrielova E., Maksimenko O.</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by-nc/4.0</ali:license_ref></license></permissions><self-uri xlink:href="https://journals.rudn.ru/linguistics/article/view/26000">https://journals.rudn.ru/linguistics/article/view/26000</self-uri><abstract xml:lang="en"><p style="text-align: justify;">The current research answers the question how Twitter users express their evaluation of topical social problems (explicitly or implicitly) and what linguistic means they use, being restricted by the allowed length of the message. The article explores how Twitter users communicate with each other and exchange ideas on social issues of great importance, express their feelings using a number of linguistic means, while being limited by a fixed number of characters, and form solidarity, being geographically distant from each other. The research is focused on the linguistic tools employed by Twitter users in order to express their personal attitude. The subject chosen for study was the migration processes in Europe and the USA. The aim of the current investigation is to determine the correlation between the attitudes of English-speaking users towards migration and the way they are expressed implicitly or explicitly. The authors make an attempt to define which tools contribute to the implicit or explicit nature of the utterances. The material includes 100 tweets of English-speaking users collected from February 1 to July 31, 2017. The choice of the time period is defined by significant events in Trump’s migration policy and their consequences. The research is based on the content analysis of the material carried out by means of the Atlas.ti program. The software performs the coding of textual units, counts the frequency of codes and their correlation. The results of the research show that Twitter users tend to express their critical attitudes towards migration, rather than approve of it or sympathise with migrants. Criticism is more often expressed implicitly rather than explicitly. In order to disguise the attitude and feelings, the English-speaking users of Twitter employed irony, questions and quotations, while the explicit expression of attitudes was done by means of imperative structures. It is also worth mentioning that ellipses, contractions and abbreviations were used quite frequently due to the word limit of tweets. At the same time, the lack of knowledge about extralinguistic factors and personal characteristics of users makes the process of interpretation of tweets rather challenging. The findings of the current research suggest the necessity to take into account implicit negative attitudes while carrying out the analysis of public opinion on Twitter.</p></abstract><trans-abstract xml:lang="ru"><p style="text-align: justify;">Данное исследование отвечает на вопрос, каким образом (имплицитно или эксплицитно) и при помощи каких лингвистических средств пользователи Twitter выражают свое мнение об актуальной социальной проблеме в условиях ограниченности количества символов в сообщении. В статье подробно рассматривается влияние ограниченного количества символов в сообщении Twitter на выбор лингвистических средств пользователями для выражения своего мнения и эмоциональной оценки социально значимого события. Исследование сфокусировано на способах выражения оценки проблемы миграции в Европе и США англоязычными пользователями микроблога Twitter. Цель исследования заключается в установлении связи между эксплицитным или имплицитным способом выражения оценки и ее эмоциональной составляющей (выражающей одобрение или критику). Анализ проводился посредством использования программы компьютерного контент-анализа Atlas.ti. Корпус языкового материала составил 100 твитов. Период сбора материала для анализа (февраль-июль 2017 г.) обусловлен важными событиями в миграционной политике США и ее трагическими последствиями. Результаты исследования показали, что наибольшее количество сообщений выражает негативное отношение к миграционным процессам в США и Европе, а также недовольство проводимой миграционной политикой. Критика часто имплицируется при помощи иронии, вопросительных конструкций и цитат, в то время как императивные конструкции чаще всего были использованы в эксплицитных высказываниях. Англоязычные пользователи микроблога часто используют аббревиатуры, сокращения и эллиптические конструкции, что может быть обусловлено текстовым ограничением сообщений. Авторы исследования приходят к выводу, что, несмотря на определенную анонимность, предоставляемую коммуникацией в интернет-пространстве, пользователи Twitter склонны имплицировать негативные высказывания в адрес политических структур. Интерпретация скрытых смыслов сообщений усложняется отсутствием экстралингвистических факторов и личных характеристик коммуникантов. Результаты исследования свидетельствуют о необходимости учета импликации негативной оценки при использовании микроблога Twitter в качестве источника материала для анализа общественных настроений.</p></trans-abstract><kwd-group xml:lang="en"><kwd>linguistic tools</kwd><kwd>implicit evaluation</kwd><kwd>explicit evaluation</kwd><kwd>Twitter</kwd><kwd>online communication</kwd><kwd>migration</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>миграция</kwd><kwd>лингвистические средства выразительности</kwd><kwd>имплицитная оценка</kwd><kwd>эксплицитная оценка</kwd><kwd>Twitter</kwd></kwd-group><funding-group/></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Alsaeedi, Abdullah &amp; Mohammad Zubair Khan. 2019. A study on sentiment analysis techniques of Twitter data. 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