Sentiment Analysis of Consumer Reviews of Amazon Products

Table of Contents

1. Installation
2. Project Motivation
3. File Descriptions
4. Results
5. Licensing, Authors, and Acknowledgements

Installation

The code was tested using Python version 3.9. For other necessary libraries please use requirements.txt

pip install -r requirements.txt

Please download the data from Kaggle here

Project Motivation

This project works with Amazon Reviews Data and focusses on:

1. Sentiment Analysis using Large Language Model (LLM)
2. Fine-Tuning the Large Language Model
3. Data Augmentation using Back-Translation technique
4. Data Balancing (working with imbalanced Dataset)
   • Random Oversampling
   • Weighted Loss

File Descriptions

sentiment-analysis-llm/
├── amazon reviews sentiment analysis.ipynb        # the notebook with data augmentation, data balancing, sentiment analysis and fine-tuning using (HuggingFace)
├── README.md              # readme file
├── requirements.txt       # all necessary libraries
├── Emoticon.py            # dictionary with emojis as a symbol with the text description 

Results

The main findings of the code can be found at the post:

"Sentiment Analysis of Customer Product Reviews using Large Language Model (LLM)" available here.

Licensing, Authors, Acknowledgements

Must give credit to Kaggle for providing the data.

Copyright (C) 2024 February

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