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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