https://github.com/iguptashubham/twiiter-sentiment-analysis

"Twitter Sentiment Analysis", is like a mood detector for Twitter. I use Python and library called NLTK (Natural Language Toolkit) to help understand the language in the tweets. It's like a translator that helps your code understand human language
https://github.com/iguptashubham/twiiter-sentiment-analysis

Last synced: 3 months ago
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"Twitter Sentiment Analysis", is like a mood detector for Twitter. I use Python and library called NLTK (Natural Language Toolkit) to help understand the language in the tweets. It's like a translator that helps your code understand human language

• Host: GitHub
• URL: https://github.com/iguptashubham/twiiter-sentiment-analysis
• Owner: iguptashubham
• Created: 2024-01-05T14:00:43.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-01-05T14:03:18.000Z (over 1 year ago)
• Last Synced: 2025-01-14T04:14:07.566Z (4 months ago)
• Language: Jupyter Notebook
• Size: 1.41 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# twiiter-sentiment-analysis

![machine-learning-twitter-sentiment-analysis-negative-](https://github.com/iguptashubham/twiiter-sentiment-analysis/assets/140319219/771d9936-0a2b-4857-b41c-b2880424d38c)

 Sure, here's a simple description of your project:

 "Twitter Sentiment Analysis", is like a mood detector for Twitter. I use Python and library called NLTK (Natural Language Toolkit) to help understand the language in the tweets. It's like a translator that helps your code understand human language.

Then, I use a method called Logistic Regression to make predictions. It's like a magic 8-ball that can predict if a tweet is positive or negative based on the words in it.

So, in short, my project reads tweets, understands them using NLTK, and predicts their mood using Logistic Regression. It's a cool way to understand how people are feeling on Twitter! 😊

## WorkFlow of Project

![twitter--data-data-preprocessing-train-test-logistic](https://github.com/iguptashubham/twiiter-sentiment-analysis/assets/140319219/1b223698-2387-49b6-b6ab-d0218c92108e)