In this course, you are introduced to the topic of communication in the digital society. The course provides a brief overview of the classical communication science paradigms and introduces the technological and societal characteristics of the digital society. You will discuss the implications of these characteristics for existing communication theories.

This course provides an introduction to the computational methods and practices that allow researchers and practitioners to study different phenomena in the digital society. You receive a comprehensive introduction to programming in Python for data science, including best practices for data wrangling, generating basic descriptive and inferential statistics, as well as data visualization in Python.

This course focuses on computational techniques behind new digital ways of communication and provides a basic understanding of their design principles, implications, and teaches how these methods can be used for science. You will work with some of these methods yourself in the weekly tutorials to get hands-on experience with these techniques and experience the advantages and limitations first-hand.

You can choose one of the four elective courses that focus on different aspects of communication in the digital society: “Topic All things media? Emerging communication technologies and their impact on us and society”, “Topic Always Connected: Key insights in youth, media and technology”, “Topic Health Communication: From Theory to Practice”, “Topic Algorithmic Persuasion in the Digital Society”.

In the final course of this minor you will apply the theoretical knowledge, methodological skills and critical attitude developed during the previous courses of the minor into a group research project.