Project Study in Data Science and Quantitative Methods
Course Objectives and Overview
This project-centered course introduces students to the use of data science and large-scale data in addressing contemporary social and economic challenges. Students will learn how to structure and execute an empirical research project, from defining a research question to communicating results. A core component of the course is the development of an interactive web application to present findings in a clear and engaging way.
Students will work in groups of three to four and are expected to take substantial responsibility for shaping and managing their projects. The course concludes with a public presentation of results, a complete web application, and a written project report. Students will also provide constructive feedback on the work of other groups.
Project Phases
Phase 1: Introduction and Project Selection
The course begins with a kick-off meeting that introduces the goals, structure, and expectations of the seminar. We will examine pressing social and economic issues and discuss how data science methods can contribute to understanding and addressing them. Students will then identify their research topic, formulate their research question, and submit a brief project proposal one week later.
Phase 2: Research Development and Analysis
After project proposals are approved, groups will develop their research design, collect and explore data, and conduct their empirical analysis. Students will first present descriptive statistics and later their analytical results. In parallel, students will receive training in building interactive web applications using Shiny for R to prepare for the final presentation of results.
Phase 3: Presentation and Dissemination
In the final stage of the course, groups will present their findings and critically reflect on their implications. Each group will deliver:
- A fully functioning Shiny web application that communicates their results to a broader audience (e.g., researchers, policymakers, or stakeholders)
- A written project report summarizing the research question, data, methods, results, and conclusions
Projects from previous years
The Manifesto Project: Examining Populism in Germany
By Lena Hermann, Chiara Döring and Roger Schneider
Analyzes populist patterns in German party manifestos from 1981 to 2021
(Further information can be found at sebastian-weibels.shinyapps.io/Populism-Elections/)
The Role of Sustainability Dimensions in Predicting Election Results
By Mira Belhenniche, Jean-Patrick Pallagi, Amelie Wöstmann and Klara Spielmann
Analyzes how varying emphases on different dimensions of sustainability within the manifestos of EU party families associate with their electoral outcomes
(Further information can be found at sebastian-weibels.shinyapps.io/Sustainability-Elections/)
What Shapes Trust in the European Union in Poland, Germany, and Slovenia?
By Helena Zappe and Marei Göbelbecker
Examines the factors influencing trust in the European Union across Poland, Germany, and Slovenia
(Further information can be found at sebastian-weibels.shinyapps.io/TrustEU/)
European Social Survey Immigration Dashboard
By Lena Tischler, Helen Kreuzer and Katharina Veerhoff
Explores the influences on differences in attitudes toward migration across countries and over time
(Further information can be found at sebastian-weibels.shinyapps.io/ImmigrationEU/)
