COMPUTATIONAL SOCIAL SCIENCE AND INFORMATION SYSTEMS: ANALYZING DIGITAL FOOTPRINTS IN SOCIETY

Abstract

Computational Social Science (CSS) has emerged as a multidisciplinary field that uses computational tools to analyze social phenomena. This research focuses on understanding how digital footprints—such as online interactions, social media engagement, and e-commerce activity—reflect societal behavior and trends. With the advent of Information Systems (IS) in the digital age, analyzing vast amounts of social data has become feasible. This paper investigates how digital footprints shape modern societies and how computational methods are utilized to extract meaningful patterns. The study examines data collection techniques, data processing methods, and the implications of analyzing digital traces for public policy, marketing, and social behavior. Keywords such as computational social science, digital footprints, information systems, and social behavior serve as the foundation for this research. The findings underscore the need for interdisciplinary approaches to study social interactions in the digital world, offering insights into the evolving dynamics of modern society.