humanitiesГуманитарные науки. Вестник Финансового университетаHumanities and Social Sciences. Bulletin of the Financial University2226-78672619-1482Financial University under The Government of Russian Federation10.26794/2226-7867-2022-12-3-36-40humanities-682Research ArticleФУНДАМЕНТАЛЬНОЕ НАУЧНОЕ ЗНАНИЕFUNDAMENTAL SCIENTIFIC KNOWLEDGEСоциологические исследования в цифровую эпоху: формирование базы знаний вычислительной социологииSociological research in the digital age: forming the Knowledge base of Computational sociologyhttps://orcid.org/0000-0002-9876-015XРафиковаК. Ф.RafikovaK. F.

Ксения Фуатовна Рафикова — аспирант философско-социологического факультета Института общественных наук; преподаватель кафедры теоретической социологии и эпистемологии философско-социологического факультета Института общественных наук

Москва

Ksenia F. Rafikova — Postgraduate student in the Department of Philosophy and Sociology, Institute for Social Sciences; professor of the Department of Theoretical Sociology and Epistemology, Faculty of Philosophy and Sociology, Institute for Social Sciences

Moscow

KseniyaRafikova@yandex.ruРАНХиГС при Президенте РФРоссияRANEPARussian Federation2022101020221233640Copyright © Рафикова К.Ф., 20222022Рафикова К.Ф.Rafikova K.F.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://humanities.fa.ru/jour/article/view/682

Непрерывный рост больших массивов данных и достижения в области компьютерных наук способствуют развитию такой отрасли знания, как вычислительная социология. У исследований, выполненных с использованием вычислительных методов для анализа больших данных, имеется высокий потенциал. Однако для создания теоретической базы вычислительной социологии необходимо провести множество фундаментальных наработок. В данной статье предлагается создать базу знаний для вычислительной социологии. В ней собраны исследования, выполненные с применением вычислительных и математических методов, а также связанные с моделированием, машинным обучением и анализом социальных сетей. Существует ряд ограничений для использования таких методов в социальных науках, однако они значительно расширяют исследовательское поле.

The continuous growth of big data and developments in computational sciences have contributed to the development of such an area of knowledge as computational sociology. Research performed using computational methods to analyse big data have great potential. However, a lot of fundamental work needs to be done to establish the theoretical basis of computational sociology. This paper aims to build a knowledge base for computational sociology. It brings together research done using computational and mathematical methods, as well as related to modelling, machine learning, and social networks analysis. There are several limitations of employing such methods in the social sciences, but they significantly expand the research field.

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