The Journal of Philological Studies The Journal of Philological Studies Журнал филологических исследований 2500-0519 99149 Сравнительно-историческое, типологическое и сопоставительное языкознание COMPARATIVE-HISTORICAL, TYPOLOGICAL AND COMPARATIVE LINGUISTICS Сравнительно-историческое, типологическое и сопоставительное языкознание Sentiment Analysis Based on Dictionaries: Current and Future Trends from PubMed collection Анализ тональности текстов на основе словарей: текущие и будущие тенденции по данным PubMed Шарнин М. М. Charnine Michael Michaylovich mc@keywen.com

кандидат технических наук;

candidate of technical sciences;

 Калинин С. С. Kalinin S. S. rage_of_gods@inbox.ru

кандидат филологических наук;

candidate of philological sciences;

 ФГУ «Федеральный исследовательский центр «Информатика и управление» Российской академии наук» Россия Federal Research Center Informatics and Control of the Russian Academy of Sciences Russian Federation Пермский национальный исследовательский политехнический университет Perm National Research Polytechnic University 23 05 2025 23 05 2025 10 1 41 49 23 05 2025 https://zh-szf.ru/en/nauka/article/99149/view

В работе представлено прогнозное библиометрическое исследование трендовых тем в коллекции «PubMed» в области анализа тональности текстов на основе словарей. Исследование выполнено с использованием коллекции научных статей, индексирующихся в библиографической базе данных «PubMed», из которой были отобраны 147 статей, имеющие в заголовках и аннотациях ключевые слова «sentiment analysis» (анализ тональности) и «dictionary» (словарь). Выявлен значительный рост (в 21 раз за 6 лет) ежегодно публикуемых подобных статей. Рассчитан и представлен рейтинг релевантных ключевых слов в отобранных статьях. Среди релевантных ключевых слов выявлены трендовые ключевые слова c прогнозируемым долгосрочным ростом трендов. Представлена семантическая карта трендовых ключевых слов, содержащая информацию о новизне и долгосрочности трендов. В результате визуального анализа семантической карты выявлены две трендовые темы: (1) вопросы благополучия, (2) удовлетворение пациентов и заказчиков. К вопросам благополучия относятся трендовые подтемы: одиночество, депрессия, устойчивость к подобным проблемам, стратегии их преодоления.

The paper presents a predictive bibliometric study of trending topics in the PubMed collection in the field of sentiment analysis of texts based on dictionaries. The design of the present study uses a collection of scientific articles indexed in the PubMed bibliographic database. 147 articles that had the keywords “sentiment analysis” and “dictionary” in the titles and abstracts were retrieved from the mentioned base. A significant increase (21 times over 6 years) in the number of annually published similar articles was revealed. The rating of relevant keywords in the selected articles was calculated and presented. Among the relevant keywords, trending keywords with predicted long-term trend growth were identified. A semantic map of trending keywords is drawn, containing information on the novelty and longevity of trends. As a result of visual analysis of the semantic map, two trending topics were determined: (1) well-being issues, (2) patient and customer satisfaction. Well-being issues include trending subtopics: loneliness, depression, resilience to such problems, and strategies of their coping.

 обработка естественного языка формальные языковые модели библиометрический анализ анализ тональности семантическая карта долгосрочный прогноз развития научных трендов библиографическая база данных PUBMED natural language processing formal linguistic models bibliometrical analysis sentiment analysis semantic map long-term prediction of transformation of scientific trending topics PubMed database collection

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