INTERDISCIPLINARY RESEARCH METHODS IN THE CONTEXT OF DIGITAL TRANSFORMATION: A POLICY ANALYSIS

Abstract

The article examines the role and potential of interdisciplinary research methods in policy analysis in the context of digital transformation. Information and technological changes of the 21st century require political science to employ data-driven, comprehensive, and digital approaches to analyze socio-political processes. The study analyzes the capabilities of contemporary methods such as big data, data mining, digital ethnography, discourse analysis on social media, crowdsourced political forecasting, digital cartography, and mathematical modeling. In addition, the research addresses the methodological adaptation of political studies and the impact of interdisciplinary integration with IT, sociology, psychology, linguistics, and data science on the quality of political analysis. The author also highlights issues of data reliability and the measurement of public opinion in algorithmic environments. The research results provide an opportunity for a deeper understanding of political processes in a digital society and enhance the scientific validity of political analysis.