Text Mining in R

Mining and Analyzing Twitter Data with R

The Center for Customer Insights and Digital Marketing presents this workshop as a hands-on demonstration of text mining in R. Accessing the Twitter API and using Center tweets as the data source, Junior Marketing Scientist Jarrod Griffin discusses how to clean, tidy, and tokenize text data to understand the various sentiments tweets convey. You will learn how to take sentiments from tweets and visualize textual data to gain insights into the words and phrases posted on social media. Term Frequency and Inverse Document Frequency cover how important a word is in a document. Finally, we discuss Topic Modeling which can be used to mine topics from collections of tweets.

Learning Outcomes

After the workshop, you should be able to:

1. Use R to clean text data into tidy text format

2. Analyze a set of text for sentiment

3. Create Term Frequency and Inverse Document Frequency data frames

4. Understand the concept of topic modeling

5. Create visualizations for visual analysis

Check below to view the video!