https://at-ceu.studyguide.timeedit.net/modules/DNDS5026?type=COREOur digital era offers unique opportunities and poses a fundamental challenge to academic research, specifically in the social sciences, as technological development and data production on human behavior progresses at an ever-increasing pace. Every 1.2 years, more human-driven socioeconomic data are produced than during all preceding years of human history combined and most of human activities are traced by digital devices. These new technologies, massively relying on digital data, have changed our lives in many respects, like the way we form and maintain social ties, how we participate in social activities, how we consume news and form an opinion about it. We are in the position to follow the evolution of large real-world social systems and to detect the emergence of collective social behavior "in vivo", for example to do real-time simulations and predictions about the spreading of deadly diseases or the outcome of political campaigns and elections. From a scientific point of view, clearly, several disciplines are actively engaged in this challenge, which call for a multidisciplinary effort in research and education. Social Data Science as a new field addresses the quantitative observations and understanding of social behavior of individuals, groups, and societies based on the analysis of large datasets as obtained from "digital footprints" or generated for the purpose of study.This seminar course provides a broader view on different fields where Social Data Science methods are applicable. The goal is to explain the actual questions that can be answered with a data science approach and the open debates about their broad applicability in various fields. This course will involve several guest lecturers from CEU departments and elsewhere, who will give lectures about their own disciplines. As a university wide course, it would provide an introduction to any participating students independent of their background to the actual topics of Social Data Science and to data driven research in general. It would help the students to develop a critical and reflexive view about the potentials and dangers of the applications of this field. Meanwhile, this course will serve as the first steppingstone for Social Data Science MS students towards their specialization in Applied Social Data Science, Economics, Environmental Science, Political Science and Policy.