Skip to content

This project has taken US Airlines Twitter Dataset (Training 15000 tweets & Testing 3000 tweets). It uses machine learning to classify the sentiments of tweets into positive, neutral and negative. It uses Naive-Bayes Classifier for text-classification and NLTK and SkLearn libraries in python.

Notifications You must be signed in to change notification settings

AnubhavJohri/Twitter-US-Airline-Sentiment-Analysis

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 

Repository files navigation

Twitter-US-Airline-Sentiment-Analysis

About

This project has taken US Airlines Twitter Dataset (Training 15000 tweets & Testing 3000 tweets). It uses machine learning to classify the sentiments of tweets into positive, neutral and negative. It uses Naive-Bayes Classifier for text-classification and NLTK and SkLearn libraries in python.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published