Computational Social Science

Algorithmic thinking in the public interest: navigating technical, legal, and ethical hurdles to web scraping in the social sciences

Web scraping, defined as the automated extraction of information online, is an increasingly important means of producing data in the social sciences. We contribute to emerging social science literature on computational methods by elaborating on web …

RVerbalExpressions: A Helpful Tool for Learning Regex in R

In a previous post, I explained how we can use regular expressions or "regex" in R to parse our text data. Turns out there is a very useful R library for crafting regular expressions, especially in the early stages of learning the notation.

Exploratory Data Analysis Using TF-IDF

Computational text analysis can be a powerful tool for exploring qualitative data. In this blog post, I'll walk you through the steps involved in reading a document into R in order to find and plot the most relevant words on each page.

A new R library for preprocessing text data

While analyzing text data can be a lot fun, preprocessing text data is generally not. It can also be extremely difficult, especially when you're just getting into computational text analysis or the R programming language.

Sampling the Canadian Hansard Dataset

Recently I learned about an incredible initiative launched by a team of political scientists, computer scientists, and historians at my university called The Canadian Hansard Dataset. The data set is a massive, digital collection of English-language debates in the House of Commons from 1901 to today (all French speeches have been translated to English).

Parsing your .pdfs in R

In my last blog post, we discussed how to read .pdf files into RStudio. Using pdftools, we were able to read in .pdfs that were both machine-ready and not.

Getting your .pdfs into R

Doing quantitative text analysis often means working with documents in .pdf format, and these documents may or may not be in a machine-readable format. Assuming we are using RStudio, how do we read these files into our environment so that we can clean, process, and analyze them?

Interactive maps and tables in R

Code and tutorial prepared for the Toronto Data Workshop session on July 30, 2020. You can download the corresponding slide deck for this workshop here. Since launching the Policing the Pandemic Mapping Project with Alexander McClelland, a lot of people have asked us how we built the interactive map and database.