Big data analysis in psychology and social sciences: Perspective directions of research

Abstract

The consequences of Big Data revolution for psychology and social sciences are analyzed. The article presents an overview of the four types of psychological research based on the Big Data analysis: Secondary data analysis; crowdsourcing projects and matching of personal digital footprints of social network users with data of psychometric questionnaires; research of psychological phenomena based on network analysis, natural language processing and machine learning without surveys; natural experiments and data gathering by portable gadgets. A special attention is paid to psychological profiling of personality by digital footprints. The perspective directions for further research of dynamics in socio-psychological phenomena at the personal, interpersonal, group, and macro-social levels with applying computer linguistic and visual data analysis are proposed. The psychological and social risks of Big Data based technologies adoption in the everyday life of society are discussed.