Course Description

Over the last decade, both the variety and amount of data available to social scientists have expanded. These new data sources include administrative records e.g., voter files, campaign finance and lobbying records, geo-referenced data e.g., satellite maps, geocoded event data, and texts e.g., speeches, court rulings, legislative bills. Many of these data sources can be accessed through the web and as a consequence, techniques such as web scraping have become an essential part of a social scientist's toolkit.

Course Objectives

The objective of this workshop is to introduce basic tools and techniques for automatic content extraction from the web, parsing, and other data-handling tasks that are commonly encountered in data-intensive research projects.

Schedule

This year, the 5-day workshop will be divided into 3 sections. You can register for all or any of the sections you require.

Section 1: Introduction to Python.
Section 2: Introduction to web scraping using R. This section presupposes prior experience using R.
Section 3: Introduction to web scraping and text processing using Python. This section presupposes prior experience using Python.

Registration

If you are interested in attending this workshop, you must register.  Please sign up here. You will be added to the Blackboard class which will give you access to materials and the discussion board.