Computational Social Science is an interdisciplinary field that studies society and human behaviour through computational analyses and large-scale data. Throughout this BSc course, students in Artificial Intelligence and Data will familiarise with topics and approaches that are central to the discipline and will learn techniques to collect, analyse and model behavioural data for tackling social science questions.
We will focus on theoretical aspects via lectures and reading, but the course has also a strong practical component, including programming exercises and a project assignment.

How the course works

The course is organized in two parts.

Lectures (Feb 1st to Mar 22nd)

Classes are thought in a flipped classroom style. Every week, you will have access to a Jupyter Notebook that contains all the material for each class, including the video lectures and the exercises. You will be able to view the video lectures before (or during) the class session, so the in-class time can be devoted to exercises, projects, and discussions.

Project work in groups (Mar 29th to May 5th)

During the last four weeks, you will work on developing a group project assignment, which involves the analysis of a dataset and a topic of your choice.

Assignments

The final grade is given on the basis of four homework assignments.

Assignments 1 and 2

There will be two written homework assignments. These consist of a subset of the exercises you have worked on during the class. This means that, if you solve the exercises each week, the assignments will be easy. You can submit all assignments on DTU Learn.

Assignment 1
Posted: During Lecture 4
Due: Tuesday, Feb 28th, 23:59

Assignment 2
Posted: During Lecture 8
Due: Tuesday, Mar 28th, 23:59

Project Assignment

In the last four weeks, you will work on developing a group project assignment. In the project, you should explore a computational social science topic of your choice, through the analysis of a suitable dataset. You should choose a relevant dataset that can be studied using the tools we have learned in class.

Project Assignment A
The first part of the final project is a 5 minutes presentation, where your group should explain the central idea/concept that you will investigate in your final project. You’re making the presentation so that I can give you feedback, and so that other groups can ‘steal’ your ideas (and you can steal ideas from them).

Slides Due: Tue, Apr 18th, 23:59
Presentation: Wed, Apr 19th, during class

Project Assignment B
The deliverable for the final assignment will be:

• A website The website should tell the story about the data that you have analysed. The website should not be technical, but rather aim at using visualization and explanation to get your insights across to a non-scientific reader.

• An explainer notebook The Notebook should contain the core of your work, including details and reflections on the dataset and the analyses, plus all the code.

Due: Sun, May 7th, 23:59