Political Behavior and Digital Media
This seminar introduces students to the study of political behavior on digital media in preparation for the research seminar in the summer term. 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 quantitative 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 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.
AI and Politics
The increasing digitalization of our everyday lives, from smartphones to social media, e-commerce or digital public services, is generating an unprecedented amount of data. Fueled by these big data, AI approaches are becoming more and more prevalent. Algorithms affect the way we interact with each other and obtain information which has important implications for social and political processes. At the same time, there are serious concerns related to AI approaches, including their inherent biases and unwanted consequences of algorithmic decision making but also a lack of effective regulation and safeguards. This workshop will first provide an overview of the current state of big data and AI including technical, ethical and regulatory challenges. Working in smaller groups, you will then deepen your knowledge by working on case studies and developing concrete concepts for the responsible use of big data and AI approaches in politics. The block course is designed as a conceptual primer for anyone interested in attaining a basic understanding of AI and politics and does not entail any technical training. There are no prerequisite requirements for this course.
PhD Workshop | Spatial Data Analysis
This workshop introduces spatial data analysis and its applications in quantitative social science research and is intended for PhD researchers. The first part will cover some of the foundations of spatial data analysis including basic concepts and definitions but also common methodological challenges (e.g., MAUP, aggregation problems). The remainder of the workshop then focuses on practical challenges for using spatial data, including integration of different spatial data types, the proper handling of event data and their deduplication. And in the last part we cover a number of more recent techniques for quantitative inference in highly disaggregated spatial settings and discuss associated best practices. Many of the examples are drawn from research on sub-national dynamics of conflict where spatial data has been extensively used in recent years but they translate to any other comparable empirical setting. The first two days of the workshop consist each of a condensed lecture-style introduction followed by a practical session in R. The last day focuses on current topics and we will discuss a few select research designs brought by participants. This is an applied workshop and you are encouraged to bring your own projects using spatial data and tackle them as part of the workshop. If you are interested to bring your own research design for the final session, please contact the organizers. For those requiring credits from the workshop, there will be the option to hand in a small final assignment that will be graded on a pass/fail basis.
PhD Workshop | Big Data and AI
The increasing digitalization of our everyday lives, from smartphones to social media, e-commerce or digital public services, is generating an unprecedented amount of data. Fueled by these big data, AI approaches are becoming more and more prevalent and have proved to be remarkably powerful in certain areas. At the same time, there are serious concerns related to AI approaches, including their inherent biases and unwanted consequences of algorithmic decision making but also a lack of effective regulation and safeguards. This workshop will first provide an overview of the current state of big data and AI including technical, ethical and regulatory challenges. Working in smaller groups, you will then deepen your knowledge by working on case studies and developing concrete concepts for the responsible use of big data and AI approaches in diverse decision-making contexts.