Digital Data in Political Science

After having completed the course, the students have acquired the following knowledge, skills and general competencies:

Knowledge

You will:

• be able to identify potential digital data-sources and develop strategies for collecting these;
• learn best practices for documenting the data-collection process;
• learn how to make your research fully reproducible;

Skills

You will:

• master several different digital data-collection techniques;
• know how to organize and document large quantities of data;
• be able to write R-code to automate all relevant stages of the research process;
• be able to create effective visualizations of the results for your analysis;
• be able to communicate academic knowledge in writing and orally.

General competencies

You will:

• become equipped to reflect upon ethical dilemmas arising in political data science;
• be able to design digital research projects that are in compliance with data-protection regulations;
• learn how to effectively collect, manage, analyze, and visualize digitally collected data.

Compulsory activities

• Attend at least seven of ten seminars.

In the event of illness or other valid reasons, you can apply for a valid absence or postponement of compulsory activity.

Apply for valid absence from or need for postponement of compulsory activity

Online resources

https://pages.github.uio.no/oyvinsti/STV4030A/

Hackathon-style seminars where students may cooperate to solve a political data science challenge. Ahead of the seminar, you will be exposed to a combination of short video lectures, online tutorials and readings in order to be prepared to attempt the weekly challenge.

Portfolio exam.

You must have passed the compulsory activities in order to sit the exam.

Pevious exams and examination guidelines