https://github.com/arulkumarann/product-review-sentiment-analysis

https://github.com/arulkumarann/product-review-sentiment-analysis

Last synced: 9 months ago
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• Host: GitHub
• URL: https://github.com/arulkumarann/product-review-sentiment-analysis
• Owner: arulkumarann
• Created: 2023-10-13T14:51:21.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-10-13T15:04:52.000Z (over 2 years ago)
• Last Synced: 2025-03-29T06:17:30.220Z (about 1 year ago)
• Language: Jupyter Notebook
• Size: 8.79 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# product-review-sentiment-analysis

##Project description

Our goal is to develop a machine learning model that can accurately classify

product reviews into one of three sen􀆟ment categories: posi􀆟ve, nega􀆟ve, or neutral. Sen􀆟ment

analysis, also known as opinion mining, is a fundamental task in natural language processing (NLP)

and can provide valuable insights for businesses to understand customer opinions and sen􀆟ments

regarding their products.

## Prerequsites

- Python3

- NLTK Library

- Pandas

- Numpy

- Product review dataset

## Installation

1. Clone this repository

2. Install required packages: 'pip install -r requirements.txt'

3. Download the NLTK Lexicon: 'nltk.download('vader_lexicon')

## Usage

- Load and preprocess your product review data as shown in the example notebook.

- Use the provided sentiment analysis tool to analyze the reviews.

- Interpret the results to understand sentiment polarity.

## Data

The sample product review dataset used in this project can be found at [https://www.kaggle.com/code/robikscube/sentiment-analysis-python-youtube-tutorial/input ].

## Results

Sample results from the sentiment analysis are as follows:

Positive: 0.75

Negative: -0.25

Neutral: 0.03

## Contributing

Feel free to contribute to this project.