🤗🤗 2024 GESIS Fall Seminar
Dr. John McLevey
University of Waterloo
Waterloo, ON, Canada
johnmclevey.com
john.mclevey@uwaterloo.ca
Hi! This repository contains a Python package and course materials for my GESIS Fall Seminar course Introduction to Computational Social Science with Python. This course is taught in parallel with Dr. Johannes Gruber, who is teaching a similar introductory course in R. You'll find the course overview and details below, along with details instructions on how to setup your computing environment.
- Course Description
- Course Schedule
- Download the Course Materials
- Using the Course Materials
- Required Software
- See the Setup Guide for more a detailed guide
The Digital Revolution has produced unprecedented amounts of data that are relevant for researchers in the social sciences, from online surveys to social media user data, travel and access data, and digital or digitized text data. How can these masses of raw data be turned into understanding, insight, and knowledge? The goal of this course is to introduce you to Computational Social Science with Python, a powerful programming language that offers a wide variety of tools, used by journalists, data scientists and researchers alike. Unlike many introductions to programming, e.g., in computer science, the focus of this course is on how to explore, obtain, wrangle, visualize, model, and communicate data to address challenges in social science. The course emphasizes the theoretical and ethical aspects of CSS while covering topics such as web scraping (obtaining data from the internet), data cleaning and visualization, computational text analysis, machine learning, network analysis, and agent-based modeling. The course will be held as a blended learning workshop with video lectures focused on theoretical background and demonstrations accompanied by live sessions where students can ask questions and work through projects together.
Working knowledge of Python is an asset, but is not required. There is an optional "Introduction to Python" module that you should review before beginning this course.
GESIS Fall Seminar in Computational Social Science
August 30 - September 6, 2024
| time | Session | Tutorial Repositories | Videos |
|---|---|---|---|
| Day 1 | Introduction to Computational Social Science | setup guide | Moodle Site |
| Day 2 | Obtaining Data | tutorials | Moodle Site |
| Day 3 | Computational Text Analysis | tutorials | Moodle Site |
| Day 4 | Computational Network Analysis | tutorials | Moodle Site |
| Day 5 | Social Simulation & Agent-based Models | tutorials | Moodle Site |
| Day 6 | Project Work Day | Moodle Site |
- Optional Additional Modules
- Introduction to Python
- Python Programming: The Basics
- Python Programming: Data Structures, Functions, and Files
- Processing Structured Data with Pandas
- Obtaining Data from the Web
- Scraping the Web (Coming soon...)
- Working with APIs (Coming soon...)
- Introduction to Python
Please consult the detailed setup guide for more information. If you run into any problems, I'll help you get them sorted in the live sessions or on the course forums on the Moodle site.
You will need a GitHub account to use the course materials in GitHub CodeSpaces. That's all you need, but you may want to download and install VS Code on your machine instead of working with VS Code in your browser. See the setup guide for detailed instructions.