Sentiment Analysis on MongoDB Messages

📌 Overview

This project connects to a MongoDB database, retrieves messages, and performs sentiment analysis using a pre-trained BERT model. The analyzed messages are displayed along with their respective sentiments.

✨ Features

• ✅ Connects to a local MongoDB database (alumni_database).
• ✅ Retrieves messages from the messages collection.
• ✅ Analyzes sentiment using the nlptown/bert-base-multilingual-uncased-sentiment model.
• ✅ Sorts messages by timestamp in descending order.
• ✅ Outputs the message details along with sentiment classification.

Sentiment Mapping

Stars Sentiment ⭐ Very Negative ⭐⭐ Negative ⭐⭐⭐ Neutral ⭐⭐⭐⭐ Positive ⭐⭐⭐⭐⭐ Very Positive

⚠️ Error Handling

• If sentiment analysis fails, an error message is displayed instead of the sentiment label.
• If fields are missing in MongoDB documents, they are replaced with placeholder values.

📋 Prerequisites

Make sure you have the following installed before running the script:

• Python 3.8+
• MongoDB installed and running locally
• Required Python libraries:

  pip install pymongo torch transformers
  

Usage

Ensure MongoDB is running. -Run the script:

  python sentimentanalysis.py