Text Analysis Using R<https://datamatters.org/course-descriptions/>, a two-day short course to be held remotely from August 12-13, 2021, is part of Data Matters: Data Science Short Course Series<http://datamatters.org>, a five-day intensive virtual course series of one-day and two-day courses for students and professionals interested in gaining skills in data science, analytics, and visualization. Registration is open at datamatters.org<http://datamatters.org>

Text Analysis Using R<https://datamatters.org/course-descriptions/>
Instructor: Alison Blaine<https://datamatters.org/instructors/>
Summary
This virtual course explains how to clean and analyze textual data using R, including both raw and structured texts. It will cover multiple hands-on approaches to getting data into R and applying analytical methods to it, with a focus on techniques from the fields of text mining and Natural Language Processing.

Why Take This Course?
The skills required to analyze textual data are useful in a wide array of academic disciplines and industries. This course will provide students already familiar with R with some of the programming skills necessary to take more control over their data analysis process and feel empowered to dive deeper.

What Will Participants Learn?
Participants will learn how to load text-based data into R, how to format and process the data for analysis, and then how to apply multiple methods for analyzing those texts. The instructional approach is to teach a concept by going step-by-step through exercises with lots of opportunities to practice concepts learned.

Prerequisites and Requirement
This course is best suited for those who already have a basic working knowledge of R. Students with no knowledge of R should consider taking an introductory R short course. Two options are the “Basics of R for Data Science” (Monday-Tuesday) or “Introduction to R for Data Science” course (Monday-Tuesday).

If you have questions regarding Data Matters, please contact Dawn Shelton ([log in to unmask]<mailto:[log in to unmask]>) or Jill Stevens ([log in to unmask]<[log in to unmask]" target="_blank">https:[log in to unmask]>).

Data Matters is sponsored by the Odum Institute for Research in Social Science at UNC-Chapel Hill, the National Consortium for Data Science, and UNC RENCI.






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