Political Science

ORCiD

What is political science?

Political science deals with institutions, democracy, social structures, international relations, political philosophy and political content. Questions are answered, such as

What are my specialties?

I deal with political behaviour, political data journalism, quantitative methods and the statistical program R.

In political behaviour, I am interested in topics such as elections and voting, participation and (the influence of) education. Data journalism is a very young discipline with great potential, especially in Germany. Everything that is current or new is interesting. In quantitative methods I deal with regression analyses and their interpretation, experiments and statistical learning.

Lectures

Fall 2021: R Pro­gramm­ing Skills (MA). Syllabus Link to Lecture

This course gives an introduction into programming and computer science. The goal is to write better code in R and be able to share useful new functions with the whole R community. We start with tidyverse, followed by basic concepts (sequence, branch, loop) and learn when and how to write a function. We then see how we can write efficient and parallel code to make it faster. We look at a tool that helps us evaluate different code against each other to see which is faster. We then see how we can create in R Package and upload it to GitHub and CRAN. After that we will look at how to write a generic S3 function and object- oriented code together with the basic concept of it. At the end will spend some time with SQL and see how we can us it in R to read and write data from and to a MariaDB database.

Fall 2021: Advanced Sta­tis­tics (BA) (in German). Syllabus Link to Lecture


Much of political science involves statistical modeling. For example, we have an outcome (e.g., social spending) and try to explain it using a set of predictor variables (e.g., left party strength). Of all statistical models, linear regression analysis remains the workhorse of political science. In this module, students learn about this model and its extensions. Emphasis is placed on formulating models, programming them in R, diagnosing assumptions, and interpreting and communicating results. Practical examples will be used throughout the course.

Spring 2021: Webprogramming and Datavisualisation (MA) (in German). Syllabus Link to Lecture

The course provides an introduction to web development. First we go through HTML, which is the foundation of the web. Then we discuss how CSS can be used to layout the web page and differentiate between mobile and desktop design. After this introduction we will dive into PHP and SQL to get an insight into backend programming. At the end of the seminar, we will spend several weeks on front-end development, learning JavaScript. The focus will be on the JavaScript library D3 and we will learn how to use it to create interactive graphics/maps. As a proof of achievement the participants have to program their own website with a blog post and an interactive graphic. The website can be started in the first few weeks. This allows the newly learned skills to be applied directly. The course requires a lot of effort from the students during the semester, because programming can only be learned with a lot of practice.

Fall 2020: R Programming Skills (MA). Syllabus Link to Lecture

This course gives an introduction into programming and computer science. The goal is to write better code in R and be able to share useful new functions with the whole R community. We start with tidyverse, followed by basic concepts (sequence, branch, loop) and learn when and how to write a function. We then see how we can write efficient and parallel code to make it faster. We look at a tool that helps us evaluate different code against each other to see which is faster. We then see how we can create in R Package and upload it to GitHub and CRAN. After that we will look at how to write a generic S3 function and object- oriented code together with the basic concept of it. At the end will spend some time with SQL and see how we can us it in R to read and write data from and to a MariaDB database.

Spring 2020: Webprogramming and Datavisualisation (MA) (in German). Syllabus Link to Lecture

The course provides an introduction to web development. First we go through HTML, which is the foundation of the web. Then we discuss how CSS can be used to layout the web page and differentiate between mobile and desktop design. After this introduction we will dive into PHP and SQL to get an insight into backend programming. At the end of the seminar, we will spend several weeks on front-end development, learning JavaScript. The focus will be on the JavaScript library D3 and we will learn how to use it to create interactive graphics/maps. As a proof of achievement the participants have to program their own website with a blog post and an interactive graphic. The website can be started in the first few weeks. This allows the newly learned skills to be applied directly. The course requires a lot of effort from the students during the semester, because programming can only be learned with a lot of practice.

Fall 2019: R Programming Skills (MA). Syllabus Link to Lecture

This course gives an introduction into programming and computer science. The goal is to write better code in R and be able to share useful new functions with the whole R community. We start with the basic concepts (sequence, branch, loop) and learn when and how to write a function. We then see how we can write efficient and parallel code to make it faster. We look at a tool that helps us evaluate different code against each other to see which is faster. We then see how we can create in R Package and upload it to GitHub and CRAN. After that we will look at how to write a generic S3 function and object-oriented code together with the basic concept of it. At the end will spend some time with SQL and see how we can us it in R to read and write data from and to a MariaDB database.

Spring 2019: Webprogramming and Datavisualisation. Syllabus Link to Lecture

The course provides an introduction to web development. First we go through HTML, which is the foundation of the web. Then we discuss how CSS can be used to layout the web page and differentiate between mobile and desktop design. After this introduction we will dive into PHP and SQL to get an insight into backend programming. At the end of the seminar, we will spend several weeks on front-end development, learning JavaScript. The focus will be on the JavaScript library D3 and we will learn how to use it to create interactive graphics/maps. As a proof of achievement the participants have to program their own website with a blog post and an interactive graphic. The website can be started in the first few weeks. This allows the newly learned skills to be applied directly. The course requires a lot of effort from the students during the semester, because programming can only be learned with a lot of practice.

Fall 2018: R Pro­gramm­ing Skills. Syllabus Link to Lecture

This course gives an introduction into programming and computer science. The goal is to write better code in R and be able to share useful new functions with the whole R community. We start with the basic concepts (sequence, branch, loop) and learn when and how to write a function. We then see how we can write efficient and parallel code to make it faster. We look at a tool that helps us evaluate different code against each other to see which is faster. We then see how we can create in R Package and upload it to GitHub and CRAN. After that we will look at how to write a generic S3 function and object-oriented code together with the basic concept of it. At the end will spend some time with SQL and see how we can us it in R to read and write data from and to a MariaDB database.

Spring 2018: Web Development for Data Journalists (MA) (in German). Syllabus Link to Lecture

The course provides an introduction to web development. First we take HTML, which is the basis of the web. We will then discuss how CSS can be used to layout the website and differentiate between mobile and desktop design. After this introduction, we will immerse ourselves in PHP and SQL to get an insight into backend programming. At the end of the seminar we will spend several weeks on front-end development and learn JavaScript. The focus will be on the JavaScript library D3 and we will learn how to create interactive graphics/maps.

Fall 2017: Advan­ced Sta­ti­sti­cal Models in Poli­ti­cal Ana­ly­sis using R (MA). Syllabus Link to Lecture

This course serves as an introduction to a multitude of probability models that are appropriate when the linear model is inadequate. In the first half we will focus on the statistical theory of maximum likelihood. The second half of the course discusses models that are particular relevant for comparative research, where the independence assumption of generalized linear models is often unmet. Throughout the seminar will also devote considerable time to statistical programming using R.

Papers / Term Papers

Schlegel, Benjamin (2015): Voter turnout among young voters (Term Paper MA)

Schlegel, Benjamin (2014): The Influence of Education and Occupation on Attitudes toward Globalization (Bachelor Thesis)

This bachelor thesis examines the influence of education and profession on attitudes towards globalization. With the adoption of the so-called mass immigration initiative, this topic became more explosive and topical. The method used is ordered logistic regression together with predicted probabilities. It is shown that the level of education has a high influence on the attitude towards globalization. In the case of occupation, it is shown that it does not matter how much the job can be outsourced. On the other hand, the influence of unemployment is very strong in the occupational group. Service workers, for example, are much more in favor of renegotiating the free movement of persons than nurses. It also shows that the influence of unemployment in the occupational group is higher than the person’s level of education. In occupational groups with high unemployment, the influence of education becomes insignificant.

Schlegel, Benjamin E. (2013): The dual education system of Germany and Switzerland (in German) (Essay in Swiss politics in depth BA)