DataCamp

Jump right in! Visualize polarity

Sentiment analysis helps you extract an author's feelings towards a subject. This exercise will give you a taste of what's to come!

We created text_df representing a conversation with person and text columns.

Use qdap's polarity() function to score text_df. polarity() will accept a single character object or data frame with a grouping variable to calculate a positive or negative score.

In this example you will use the magrittr package's dollar pipe operator %$%. The dollar sign forwards the data frame into polarity() and you declare a text column name or the text column and a grouping variable without quotes.

text_data_frame %$% polarity(text_column_name)

To create an object with the dollar sign operator:

polarity_object <- text_data_frame %$% 
  polarity(text_column_name, grouping_column_name)

More specifically, to make a quantitative judgement about the sentiment of some text, you need to give it a score. A simple method is a positive or negative value related to a sentence, passage or a collection of documents called a corpus. Scoring with positive or negative values only is called "polarity." A useful function for extracting polarity scores is counts() applied to the polarity object. For a quick visual call plot() on the polarity() outcome.

Examine the text_df conversation data frame.
Using %$% pass text_df to polarity() along with the column name text without quotes. This will print the polarity for all text.
Create a new object datacamp_conversation by forwarding text_df with %$% to polarity(). Pass in text followed by the grouping person column. This will calculate polarity according to each individual person. Since it is all within parentheses the result will be printed too.
Apply counts() to datacamp_conversation to print the specific emotional words that were found.
plot() the datacamp_conversation.

Take Hint (-30 XP)

Exercise

Jump right in! Visualize polarity

Instructions