Text reflects a number of emotions of the originator. Learn to extract emotions from text using the sentimentr package.
- [Instructor] The sentimentr package … also provides functions to analyze the emotions … of the reviews. … We will use it to understand emotions … in the review text. … First, we use the emotions_by function … to identify emotions for each review … and convert that into a DataFrame. … Let's run the code … and see the DataFrame created. … For each review, and for each emotion, … the results provide a score … and a count. … The count indicates the number of times a word representing … that emotion is present in the review. … The more the count, the stronger the emotion. … For example, in review number one, … the emotion type anger is present once. … In review number three, … a word representing disgust is present twice. … We will now aggregate the DataFrame … to summarize the emotions. … We aggregate count by emotion type. … Then we remove all records in the summary … where the count is zero. … Let's execute the code … and view the results. … This provides the overall emotions in the review corpus. …
Author
Kumaran Ponnambalam
Released
10/1/2019- Creating a word cloud
- Analyzing sentiment
- Extracting emotions from text
- Clustering similar entities based on text
- Using classification for supervised learning
- Recommending items to users based on text data analytics
Skill Level Intermediate
Duration
Views
-
Introduction
-
1. Word Cloud
-
Word cloud concepts1m 1s
-
Displaying the word cloud1m 29s
-
Enhancing the word cloud1m 25s
-
-
2. Sentiment Analysis
-
Sentiment analysis concepts1m 57s
-
Finding sentiment2m 35s
-
Summarizing sentiment1m 54s
-
Analyzing emotions1m 56s
-
-
3. Clustering
-
Clustering concepts1m 46s
-
Clustering hashtags1m 29s
-
Finding optimal cluster size1m 26s
-
-
4. Classification
-
Classification concepts1m 37s
-
Preparing data3m 13s
-
Building a model2m 7s
-
Running predictions1m 19s
-
-
5. Predictive Text
-
Predictive text concepts1m 16s
-
Preparing data2m 11s
-
Predicting text1m 57s
-
-
Conclusion
-
Next steps49s
-
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.
Share this video
Embed this video
Video: Analyzing emotions