Text Mining with R

Text is a valuable data type in various applications, including marketing analytics. It is often used for product reviews and social media analysis. Due to its affordability and simplicity, text is frequently used as a replacement for unstructured data. To fully leverage the potential of text, it is crucial to organize, clean, summarize, and model it effectively. This course aims to teach individuals how to utilize the latest tidy tools to start working with text efficiently. Participants will learn how to organize and visualize text, conduct sentiment analysis, and create and interpret topic maps. The course covers various aspects of data analysis using R, including text mining, textual analytics, and sentiment analysis using R. By the end of the course, participants will have gained the necessary skills to perform comprehensive text analysis and sentiment analysis in R. This course is ideal for individuals looking to enhance their understanding of text analysis and sentiment analysis and those interested in utilizing these techniques for marketing analytics purposes.

Character strings can be found at all stages of data science projects. It is possible to extract text data, clean up strings and turn numeric results into sentences that can be used in reports. It is possible to match strings with patterns. This course will show you how to disassemble strings and put them back together. You can also use stringr to match strings and extract strings using regular expressions. This is an effective way to express patterns.

Unstructured business information accounts for 70% of all the useful business information. This is often done using text data. Text mining can be applied to unstructured data to gain actionable insights. This course will introduce you to text mining using the bag of words approach. The first three chapters will cover topics essential to understanding and visualizing text data. The final chapter will allow you to use the information from the first three chapters to gain insight from two employee reviews in major tech companies.

Sentiment analysis can be added to your text mining software! Sentiment analysis is used by text miners in marketing, politics, customer service, and many other areas. This course will help you recognize positive and harmful language, and express your emotions. You will also learn how to create captivating visualizations. You will finish the course by applying your sentiment analysis skills to Airbnb reviews to determine what makes a good rental.