Sentiment Analysis for Text Documents

This project is a sentiment analysis application built with Python and Streamlit. It uses the Natural Language Toolkit (NLTK) to analyze the sentiment of text documents.

Features

• Upload a text document for analysis
• Preview the uploaded document
• Analyze the sentiment of the document
• Display the sentiment score on a meter
• Label the sentiment as Very Positive, Positive, Neutral, Negative, or Very Negative

How to Run

1. Clone this repository.
2. Install the required Python packages: pip install streamlit nltk
3. Run the application: streamlit run app1.py

Code Overview

The main functions in the code are:

• main: The main function that runs the Streamlit application.
• analyze_sentiment: This function takes a text string as input and returns a sentiment score using NLTK's SentimentIntensityAnalyzer.
• get_sentiment_label: This function takes a sentiment score as input and returns a label (Very Positive, Positive, Neutral, Negative, Very Negative) based on the score.
• display_sentiment_meter: This function takes a sentiment score as input and displays a sentiment meter using Streamlit's slider component.

Sentiment Score Range	Sentiment Label
> 75	Very Positive
35 - 75	Positive
-75 to < 0	Very Negative
-35 to -75	Negative
-35 to 35	Neutral

Contributions

Contributions to this project are welcome. Please open an issue or submit a pull request on GitHub.