We’ve just had an organization meeting for next Spring Computational Social Science teaching. We’ll organize, as planned, two classes

Simulation models

This course will cover the basics of system simulations, microsimulations and agent-based model simulations for social science. We will create such simulations in the class and discuss how to interpreted and apply those in practice.

The course is led by Matti Nelimarkka and it’s organized during 3rd period, Fridays 8-10.

Network analysis

This course will focus on applying network analysis in empirical research. This means basic descriptive statistics and metrics of networks and the visualization of a network as well as more computational approaches to study social networks (e.g., community detection and random walks).

The course is co-lead by Arho Toikka and Matti Nelimarkka and it’s organised during 4th period, Fridays 8-10.

The more concrete information of these courses will come before the start of Spring semester, including some syllabus. See the course pages for simulation and network analysis for further detail. Both classes will assume good familiarity of R or Python as they focus on hands-on skills and will include interactive workshopping as a teaching method.

Thinking about summer education

We might be organising two courses during the summer, Introduction to programming for social scientists and Data Extraction.

Rethinking data extraction class

One of the experiences in Spring 2016 class Data extraction was that the scope was too wide. We’re currently checking if we could meaningfully separate it to three separate classes

1. collecting, cleaning and preprocessing data for social science research
2. computational data analysis on textual data
3. computational data analysis on numerical data

If you have particular hopes about new classes that we should organise, now is your time to influence it!