Twitter Sentiment Analysis Machine Learning Project | Live Twitter API | NLP Series | Project#9

In this tutorial, we are performing sentiment analysis on live tweets pulled from Twitter via API using Python Tweepy. We are applying Python Library TextBlob & Natural Language Toolkit, viz, NLTK Sentiment Vader SentimentIntensityAnalyzer for Sentiment Computations..

🔥 Links to the entire series:
#1 - How to set up your own Twitter API, that enables you to pull 2 million tweets per month:    • Twitter API with Python 2022 - using ...  
#2 - A quick walkthrough to Tweepy, which is an easy-to-use Python library for accessing Twitter API:    • Tweepy Walkthrough | Twitter API v1.1...  
#3: Sentiment Analysis of Live Tweets:    • Twitter Sentiment Analysis Machine Le...  

Happy learning :)


🔥 Sections

00:00 Introduction
01:07 Solution Architecture
02:16 TextBlob - Basics
03:58 NLTK Sentiment Vader - Basics
05:07 Sentiment Analysis on Tweets
08:12 Donut Chart & Word Cloud
11:16 Let's talk Machine Learning


🔥 Resources:

Project files: https://drive.google.com/drive/folder...

Tweepy Documentation: https://docs.tweepy.org/en/stable/ind...
Twitter API 2.0 Documentation:   / twitter-api  
Twitter OAuth Comparison:   / v2-authentication-mapping  
TextBlob Sentiments Documentation: https://textblob.readthedocs.io/en/dev/
NLTK Sentiment Vader SentimentIntensityAnalyzer Documentation: https://www.nltk.org/api/nltk.sentime...

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