https://github.com/ramyacp14/sentimentanalysis

Implements a sentiment analysis model to determine the emotional tone behind text, helping understand attitudes, opinions, and emotions in online mentions.
https://github.com/ramyacp14/sentimentanalysis

machine-learning natural-language-processing nltk numpy pandas python scikit-learn

Last synced: 2 days ago
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Implements a sentiment analysis model to determine the emotional tone behind text, helping understand attitudes, opinions, and emotions in online mentions.

• Host: GitHub
• URL: https://github.com/ramyacp14/sentimentanalysis
• Owner: ramyacp14
• Created: 2022-12-18T05:08:40.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-09-06T20:01:26.000Z (4 months ago)
• Last Synced: 2024-11-13T20:42:12.256Z (2 months ago)
• Topics: machine-learning, natural-language-processing, nltk, numpy, pandas, python, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 3.49 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Sentiment Analysis Project

## Description

This project implements a sentiment analysis model using Python and Jupyter Notebook. Sentiment analysis is the process of determining the emotional tone behind a series of words, used to gain an understanding of the attitudes, opinions and emotions expressed within an online mention.

## Contents

- `Sentiment Analysis.ipynb`: Jupyter Notebook containing the main code for the sentiment analysis model.

## Requirements

(List the main libraries and dependencies here. For example:)

- Python 3.x

- Jupyter Notebook

- pandas

- numpy

- scikit-learn

- NLTK

## Installation

1. Clone this repository:

   ```

   git clone https://github.com/ramyacp14/SentimentAnalysis.git

   ```

2. Install the required dependencies:

   ```

   pip install -r requirements.txt

   ```

## Usage

1. Open the Jupyter Notebook:

   ```

   jupyter notebook "Sentiment Analysis.ipynb"

   ```

2. Follow the instructions within the notebook to run the sentiment analysis.

## Contributing

Contributions to this project are welcome. Please fork the repository and submit a pull request with your changes.

## Contact

For any questions or feedback, please contact Ramya Chowdary Patchala at [email protected]