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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="review-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">RUDN Journal of Studies in Literature and Journalism</journal-id><journal-title-group><journal-title xml:lang="en">RUDN Journal of Studies in Literature and Journalism</journal-title><trans-title-group xml:lang="ru"><trans-title>Вестник Российского университета дружбы народов. Серия: Литературоведение. Журналистика</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2312-9220</issn><issn publication-format="electronic">2312-9247</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">49461</article-id><article-id pub-id-type="doi">10.22363/2312-9220-2026-31-1-265-276</article-id><article-id pub-id-type="edn">TXFUFZ</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>REVIEWS</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>ОБЗОРЫ</subject></subj-group><subj-group subj-group-type="article-type"><subject>Review Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Sentiment Analysis in Mass Communication Research: A Systematic Review of Methods and Approaches</article-title><trans-title-group xml:lang="ru"><trans-title>Анализ тональности в исследованиях массовой коммуникации: систематический обзор методов и направлений</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2629-9157</contrib-id><contrib-id contrib-id-type="spin">2424-7595</contrib-id><name-alternatives><name xml:lang="en"><surname>Kozlova</surname><given-names>Anastasia V.</given-names></name><name xml:lang="ru"><surname>Козлова</surname><given-names>Анастасия Владимировна</given-names></name></name-alternatives><bio xml:lang="en"><p>PhD Student at the Department of General and Social Psychology</p></bio><bio xml:lang="ru"><p>аспирант кафедры общей и социальной психологии</p></bio><email>anastasia_kozlova94@mail.ru</email><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Lobachevsky University</institution></aff><aff><institution xml:lang="ru">Национальный исследовательский Нижегородский государственный университет им. Н.И. Лобачевского</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2026-04-01" publication-format="electronic"><day>01</day><month>04</month><year>2026</year></pub-date><volume>31</volume><issue>1</issue><issue-title xml:lang="en">VOL 31, NO1 (2026)</issue-title><issue-title xml:lang="ru">ТОМ 31, №1 (2026)</issue-title><fpage>265</fpage><lpage>276</lpage><history><date date-type="received" iso-8601-date="2026-04-02"><day>02</day><month>04</month><year>2026</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2026, Kozlova A.V.</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2026, Козлова А.В.</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="en">Kozlova A.V.</copyright-holder><copyright-holder xml:lang="ru">Козлова А.В.</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/literary-criticism/article/view/49461">https://journals.rudn.ru/literary-criticism/article/view/49461</self-uri><abstract xml:lang="en"><p>An analytical review of contemporary international research applying computational linguistics methods to the study of mass communication is presented. Particular focus is placed on sentiment analysis methodology as a key tool for measuring communicative influence. Based on a representative corpus of publications from the last five years, four key thematic areas are systematized: the analysis of reactions to global events (pandemics, military conflicts), the study of media effects mechanisms, research on hate speech and discrimination, and the measurement of suggestive influence in political and social communication. Special attention is paid to the comparative analysis of methods - from traditional lexicon-based approaches (VADER, LIWC) to modern transformer-based architectures (BERT). The conducted analysis reveals a persistent methodological gap between the technical sophistication of the algorithms and the depth of their socio-humanitarian interpretation. Current challenges in the field are discussed, including systemic biases in language models and the limitations of automated analysis for studying complex forms of communicative influence. Prospects for developing an interdisciplinary approach that integrates computational linguistics with media and communication theories are outlined.</p></abstract><trans-abstract xml:lang="ru"><p>Представлен аналитический обзор современных зарубежных исследований, применяющих методы компьютерной лингвистики для изучения массовой коммуникации. Основное внимание уделяется методологии анализа тональности как ключевого инструмента измерения коммуникативного воздействия. На основе репрезентативного корпуса публикаций за последние пять лет систематизированы четыре ключевых тематических направления: анализ реакций на глобальные события (пандемия, военные конфликты), изучение механизмов медиавоздействия, исследование языка вражды и дискриминации, а также измерение суггестивного влияния в политической и социальной коммуникации. Особое внимание уделено сравнительному анализу методов - от традиционных лексических подходов (VADER, LIWC) до современных архитектур на основе трансформеров (BERT). Проведенный анализ выявил устойчивый методологический разрыв между техническим совершенством алгоритмов и глубиной их социогуманитарной интерпретации. Обсуждаются актуальные проблемы области, включая системные смещения в языковых моделях и ограничения автоматического анализа для изучения сложных форм коммуникативного воздействия. Намечаются перспективы развития междисциплинарного подхода, сочетающего компьютерную лингвистику с теориями медиа и коммуникации.</p></trans-abstract><kwd-group xml:lang="en"><kwd>big data</kwd><kwd>mass media</kwd><kwd>communication</kwd><kwd>natural language processing</kwd><kwd>communicative influence</kwd><kwd>algorithmic bias</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>большие данные</kwd><kwd>средства массовой информации</kwd><kwd>коммуникация</kwd><kwd>обработка естественного языка</kwd><kwd>коммуникативное воздействие</kwd><kwd>алгоритмическое смещение</kwd></kwd-group><funding-group/></article-meta><fn-group/></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Akhter, M.M., &amp; Kanojia, D. (2023). Covid-19 public sentiment analysis for Indian Tweets classification. ArXiv, 2308.06241. https://doi.org/10.48550/arXiv.2308.06241</mixed-citation></ref><ref id="B2"><label>2.</label><mixed-citation>Bhaskaran, J., &amp; Bhallamudi, I. (2019). 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