Learning Outcomes
Session 1:
By the end of session 1 participants will …
- be able to clean, manipulate, and transform text data using the {stringr} package.
- use basic regular expressions to extract and remove patterns in text.
- convert unstructured text data into a tidy format suitable for analysis with {tidytext}.
- understand basic text mining concepts, such as tokenization and stop words.
Session 2:
By the end of session 2 participants will …
- create beautiful plots of text data including word clouds.
- be able to analyse the sentiment of a piece of text and compare sentiment across texts and over time.
- understand how to extract representative words of a text to classify its content.
- be able to understand and perform lemmatization and stemming using {textstem}.
This course does not include:
- A detailed use of the {tidyverse} packages used for data wrangling. For comprehensive coverage of the {tidyverse} see our Data Wrangling in Tidyverse course.
