Fall Term 2020

Political Behavior and Digital Media

This applied research seminar introduces students to the study of political behavior on digital media. The assigned readings cover topics ranging from relevant foundational work, for example, related to automated data extraction or social network analysis, to the current state-of-the-art of quantitative approaches for the study of political behavior online, including observational and experimental studies. Throughout the seminar, we critically discuss the strengths and limitations of different kinds of approaches. We will focus, in particular, on whether and how they can be leveraged to better understand the implications of online political behavior for (offline) social processes.


Intrastate Conflict and Terrorism

This seminar introduces students to the study of intrastate conflict and terrorism. It first covers foundational readings that introduce key theoretical explanations for these types of conflict. It then reviews the current state of our understanding of the causes and dynamics of these conflicts. The seminar places a particular emphasis on the measurement of conflict phenomena and their quantitative analysis. We will, in particular, cover the current state-of-the-art for the collection of conflict event data through a variety of institutional data collection initiatives and the corresponding analytical approaches for these kinds of micro-level data. Throughout, we critically discuss the scope of our current conceptual understanding as well as the limitations of existing data collection efforts and quantitative methodologies.


Big Data Analysis

This block course provides a basic introduction to big data and corresponding quantitative research methods. The objective of the course is to familiarize students with big data analysis as a tool for addressing substantive problems. The course begins with a basic introduction to big data and discusses what the analysis of these data entails, as well as associated technical, conceptual and ethical challenges. Strength and limitations of big data research are discussed in depth using real-world examples. Students then engage in case study exercises in which small groups of students develop and present a big data concept for a specific real-world case. These exercises are designed to familiarize students with the format of big data and to gain a first, hands-on experience with potential applications for large, complex data in policy-relevant settings. The block course is designed as a primer for anyone interested in attaining a basic understanding of what big data analysis entails and does not entail technical training for scripting etc. There are no prerequisite requirements for this course.