dtЦифровая трансформацияDigital Transformation2522-96132524-2822Educational Establishment “Belarusian State University of Informatics and Radioelectronics”10.35596/1729-7648-2026-32-1-12-18dt-1002Research ArticleЭКОНОМИЧЕСКИЕ НАУКИ, ОБРАЗОВАНИЕECONOMIC SCIENCES, EDUCATIONКлючевые факторы алгоритмов социальных сетей: классификация и практическая значимость для SMMKey Factors of Social Networks Algorithms: Classification and Practical Significance for SMMБатураМ. П.BaturaM.

д-р техн. наук, проф., зав. науч.- исслед. лаб. «Новые обучающие технологии»

Минск

Dr. Sci. (Tech.), Professor, Head of the R&D Lab “New Educational Technologies”

Minsk 

МарахинаИ. В.МаrakhinaI.

Марахина Инна Викторовна, канд. экон. наук, доц., доц. каф. экономики 

220005, Минск, ул. Платонова, 39–809, Тел.: +375 29 380-59-99

Маrakhina Ina, Cand. Sci. (Econ.), Associate Professor, Associate Professor at the Economics Department

220005, Minsk, Platonova St., 39–809, Tel.: +375 29 380-59-99

marahina@bsuir.byПархименкоВ. А.ParkhimenkoU.

канд. экон. наук, доц., зав. каф. экономики 

Минск

Cand. Sci. (Econ.), Associate Professor, Head of the Economics Department

Minsk 

Белорусский государственный университет информатики и радиоэлектроникиBelarusian State University of Informatics and Radioelectronics2026050420263211218Copyright © Батура М.П., Марахина И.В., Пархименко В.А., 20262026Батура М.П., Марахина И.В., Пархименко В.А.Batura M., Маrakhina I., Parkhimenko U.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://dt.bsuir.by/jour/article/view/1002

В социальных сетях алгоритмические системы определяют, увидят ли пользователи тот или иной контент, что требует от маркетологов выявления и анализа ключевых параметров, определяющих логику работы таких алгоритмов. В статье представлены систематизация и комплексный анализ ключевых факторов, которые алгоритмы социальных сетей учитывают при отборе, ранжировании и демонстрации текстовых, фото- и видеоматериалов. На их основе сформированы обоснованные рекомендации по оптимизации стратегий маркетинга в социальных сетях. В результате анализа выделены такие ключевые факторы, как уровень вовлеченности потребителя контента, предпочтения пользователей, соответствие контента приоритетам платформы (социальной сети), новизна контента, предыдущий успех (положительный опыт) публикаций, длительность просмотра. Предложены методические рекомендации по продвижению компании в социальных сетях с учетом каждого фактора.

On social networks, algorithms determine whether users see certain content, requiring marketers to identify and analyze the key parameters that govern the logic of these algorithms. This article presents a systematization and comprehensive analysis of the key factors that social networks algorithms consider when selecting, ranking, and displaying text, photo, and video content. Based on these factors, the recommendations for optimizing social networks marketing strategies have been developed. The analysis identified key factors such as consumer engagement, user preferences, content alignment with platform (social network) priorities, content novelty, previous success (positive experience) of publications, and viewership duration. Methodological recommendations for company promotion on social networks, taking each of these factors into account, are proposed.

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The authors declare that there are no conflicts of interest present.