Data Visualization, Web Scraping, and Text Analysis in R Summer School
Aims
Many researchers rely on data that are obtained from a wide variety of online sources, including web sites, social media, and external data providers. This course introduces you to procedures for collecting, preparing, analysing, and visualising such data. Participants will learn about core ideas in data visualization, web scraping, and text analysis while gaining practice writing, debugging, and tracking changes to code in R.
Information
There are four sessions of 4 hours each taking place on two days. Sessions will include a mix of brief lectures, coding demonstrations, and in-class exercises. You will need to bring a laptop to these sessions on which you have the necessary rights to install software. Students will work with data sets supplied for the course, as well as obtain their own data from the Internet by applying what they have learned in the course.
Assessment
Sessions are both iterative and cumulative, hence attendance for all four sessions is mandatory. During sessions, you will work on exercises allowing you to practice new skills. These exercises will not be graded, but their completion is mandatory. Between sessions, you will complete additional exercises based on your own research interests. Students will also review and replicate each other's code.
Additional info
Students are expected to satisfy the following entry requirements:
- Prior experience writing code in the R programming language.
- Use of a laptop computer with current versions of R, RTools (Windows only), and RStudio already installed
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For the timetable of this course, please click here.
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This course is fully booked.
Please note that the number of places for this course is limited. In case the number of registrations exceeds the number of available seats, priority is given to ERIM RM students and PhD candidates.
This course is free of charge for ERIM members (faculty members, PhD candidates and RM students). For external participants, the course fee is 250 euro per ECTS credit.
