4.4. * Sentiment Analysis#

Warning

This learning outcome is considered optional in [OhioDoHEducation21]. We include it here but do not develop it.

Learning Outcome

Interpret and classify emotions within text data using rule-based or machine learning algorithms which focus on polarity (negative, neutral, or positive), feelings and emotions (happy, angry, sad, etc.) and intentions (interested or not interested).

Sample Tasks

  • Identify the various types of sentiment analysis.

  • Identify, or give an example of, uses of sentiment analysis.

  • Read text from a dataset and tokenize the data.

  • Use a sentiment lexicon to analyze the sentiment for given text data.

  • Visualize the sentiment of text data using scatterplots or boxplots.

  • Use a package such as Sentiment Analysis in R to perform sentiment analysis for a given set of data.

[OhioDoHEducation21]