Conducted sentiment analysis and data visualization on YouTube comments using the TextBlob library, uncovering insights on audience engagement, emoji usage, and video performance metrics. Implemented linear regression models to explore correlations between views, likes, video titles, and audience engagement.
-
Notifications
You must be signed in to change notification settings - Fork 0
Conducted sentiment analysis and data visualization on YouTube comments using the TextBlob library, uncovering insights on audience engagement, emoji usage, and video performance metrics. Implemented linear regression models to explore correlations between views, likes, video titles, and audience engagement.
AryanBalaji/TextAnalysis
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
Conducted sentiment analysis and data visualization on YouTube comments using the TextBlob library, uncovering insights on audience engagement, emoji usage, and video performance metrics. Implemented linear regression models to explore correlations between views, likes, video titles, and audience engagement.
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published