Sentiment Analysis of Social Media Posts

This project focuses on analyzing sentiments in social media posts using Natural Language Processing (NLP). The system classifies posts into different sentiment categories such as positive, negative, and neutral.

Features

• Classify social media posts into sentiment categories: positive, negative, neutral.
• Utilizes advanced NLP techniques and machine learning models.
• Interactive interface to view and analyze sentiment results.
• Ability to handle large volumes of text data efficiently.

Installation

To set up this project on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/nlp-sentiment-analysis.git
   cd nlp-sentiment-analysis

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To start the sentiment analysis system, run the main script with your text data:

python sentiment_analysis.py