by Julia Silge

🗓️ January 27 and 28, 2020
⏰ 09:00 - 17:00
🏨 Franciscan Rooms A-B (Ballroom Level)
✍️ bit.ly/silge-rstudioconf-1 and bit.ly/silge-rstudioconf-2

Have you ever encountered text data and suspected there was useful insight latent within it but felt frustrated about how to find that insight? Are you familiar with dplyr and ggplot2, and ready to learn how unstructured text data can be analyzed within the tidyverse ecosystem? Do you need a flexible framework for handling text data that allows you to engage in tasks from exploratory data analysis to supervised predictive modeling?

Text data is increasingly important in many domains, and tidy data principles and tidy tools can make text mining easier and more effective. In this workshop, learn how to manipulate, summarize, and visualize the characteristics of text using these methods and R packages from the tidy tool ecosystem. These tools are highly effective for many analytical questions and allow analysts to integrate natural language processing into effective workflows already in wide use. Explore how to implement approaches such as sentiment analysis of texts, measuring tf-idf, network analysis of words, and building both supervised and unsupervised text models.

At the end of this course, participants will understand how to:

• Perform exploratory data analyses of text datasets, including summarization and data visualization
• Understand and implement both tf-idf and sentiment analysis
• Build classification models for text using tidy data principles

This course will be appropriate for you if you answer yes to these questions:

• Have you ever encountered text data and suspected there was useful insight latent within it but felt frustrated about how to find that insight?
• Are you familiar with dplyr and ggplot2, and ready to learn how unstructured text data can be analyzed within the tidyverse ecosystem?
• Do you need a flexible framework for handling text data that allows you to engage in tasks from exploratory data analysis to supervised predictive modeling?

During this workshop, we'll share code and slides via a GitHub repo and code interactively together using an RStudio Cloud project. You can log in to RStudio Cloud via Google credentials, GitHub credentials, or email. Go ahead and log in with your choice of method before we meet in person so you see what the platform looks like. Bring your laptop to the course and we'll explore text mining together!

Julia Silge is a data scientist and software engineer. She is both an international keynote speaker and a real-world practitioner focusing on data analysis and machine learning practice. She is an author of Text Mining with R with her coauthor David Robinson and has a PhD in astrophysics. She loves making beautiful charts and communicating about technical topics with diverse audiences.

This work is licensed under a Creative Commons Attribution 4.0 International License.