Twitter Sentiment Analysis

This project uses Natural Language Processing techniques to perform sentiment analysis on tweets from Twitter. The sentiment analysis is performed using machine learning algorithms to classify tweets as positive, negative, or neutral.

Getting Started

Prerequisites

• Prerequisites
• Python 3.7 or higher
• pip package manager

Installation

• Clone the repository

git clone https://github.com/KiranPranay/twitter_sentimental_analysis.git

• Install the required packages

pip install -r requirements.txt

Usage

• Start the Flask server

python app.python

• Open the web app in your browser by navigating to http://localhost:5000

Features

• Analyze the sentiment of a specific Twitter user's timeline
• Analyze the sentiment of tweets from a specific hashtag
• View a summary of the sentiment analysis results, including the percentage of positive, negative, and neutral tweets

Built With

• Python
• Flask
• Snscrape
• TextBlob

License

This project is licensed under the MITLicense - see the LICENSE file for details.

Acknowledgements

• Sentdex for the tutorial on which this project is based.

• TextBlob for providing an easy-to-use API for natural language processing.

• Snscrape for scraping tweets.