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This repository implements sentiment analysis using NLTK, featuring VADER sentiment scoring and a RoBERTa pretrained model. It includes a detailed comparison between VADER and RoBERTa for sentiment analysis techniques.

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Sentiment-Analyzer

This repository contains a sentiment analysis project implemented using NLTK. The project incorporates VADER sentiment scoring and a RoBERTa pretrained model for detailed sentiment analysis comparisons.

Table of Contents

Overview

The project focuses on sentiment analysis using NLTK, featuring both VADER sentiment scoring and a RoBERTa pretrained model. It includes a comprehensive comparison between these models, showcasing different approaches to sentiment analysis techniques.

Tech Stack

  • Python Libraries: NLTK, Transformers (for RoBERTa)
  • Tools: Jupyter Notebook, Google Colab

Getting Started

Prerequisites

Ensure you have the following installed on your local development environment:

  • Python 3.x
  • pip (Python package installer)
  • Jupyter Notebook (optional but recommended)

Installation

  1. Clone the repository:
    git clone https://github.com/yourusername/sentiment-analyzer.git

Usage

To start using the project, open and run the notebooks in Jupyter Notebook or Google Colab. Follow the instructions within each notebook to perform sentiment analysis using VADER and RoBERTa models, and to explore the comparison between these techniques.

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This repository implements sentiment analysis using NLTK, featuring VADER sentiment scoring and a RoBERTa pretrained model. It includes a detailed comparison between VADER and RoBERTa for sentiment analysis techniques.

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