Northwestern Events Calendar

Feb
28
2023

R Workshop Series: Intro to Webscraping and Text-As-Data in R

When: Tuesday, February 28, 2023
12:30 PM - 2:00 PM CT

Where: Scott Hall, 212, 601 University Place, Evanston, IL 60208 map it

Audience: Faculty/Staff - Student - Post Docs/Docs - Graduate Students

Contact: Ariel Sowers   (847) 491-7454

Group: Department of Political Science

Category: Academic

Description:

Please join the R Workshop Series as Political Science Ph.D. Candidate Andrés Schelp leads a session on Intro to Webscraping and Text-As-Data in R.

Have you ever wondered how to use text (such as speeches, official documents/statements, and news articles) as a data source for your research? In the workshop, we will examine how to scrape text (that does not usually exist in an easily downloadable format) step-by-step from web pages and store it in a useful way with R. We will also review some basic concepts and ideas about text-as-data and explore some of the challenges of webscraping, which to me is closer to an iterative process than an exact and straightforward method. Additionally, we will briefly explore different approaches to analyzing texts.

This session is hybrid by Zoom and in Scott Hall 212

The PS 490 R Workshop serves to introduce the R programming language and promote best practices in its use. For many years, R has been favored by a passionate user-base of social scientists and statisticians. These users have contributed many packages to simplify the task of analyzing data and reporting results. Today, R stands apart in the statistical software ecosystem because of the extensiveness and quality of these open-source libraries. In previous eras, finding such high-quality software would require using expensive, proprietary systems such as STATA or SAS. While non-academic researchers often favor other languages (notably Python), R is still regarded as very useful outside academia. While each programming language has its wrinkles, familiarity with R will make learning other languages favored by data scientists considerably easier.

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