Twitter Sentiment Analysis

Overview

This project is a Twitter sentiment analysis application built using Flask. The application allows users to analyze the sentiment of tweets based on a specific keyword or hashtag provided in a CSV file. It leverages Natural Language Processing (NLP) techniques to classify tweets as positive, negative, or neutral.

Features

• Sentiment Analysis: Analyzes the sentiment of each tweet and categorizes it as positive, negative, or neutral.
• Data Visualization: Provides visual representations of the sentiment distribution using charts.

Technologies Used

• Flask: A micro web framework for Python to build the web application.
• Pandas: For data manipulation and analysis.
• NLTK: Natural Language Toolkit for performing sentiment analysis.
• Matplotlib/Plotly: For data visualization of sentiment analysis results.
• HTML/CSS/JavaScript: For frontend development.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/twitter-sentiment-analysis.git
   cd twitter-sentiment-analysis

2. Create a virtual environment:

   python -m venv venv

3. Activate the virtual environment:

   • On Windows:

     venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

4. Install the required packages:

   pip install -r requirements.txt

Usage

1. Run the Flask application:

   python app.py

2. Open your web browser and go to http://127.0.0.1:5000.

Acknowledgments

• Pandas Documentation
• NLTK Documentation
• Flask Documentation