shaadclt/Aspect-Based-Sentiment-Analysis

This project demonstrates Aspect-Based Sentiment Analysis (ABSA) using PyABSA, a library for aspect-based sentiment analysis. The application allows users to input a sentence, and it extracts aspects, predicts sentiment, and displays the results in a tabular form.

Aspect-Based Sentiment Analysis with PyABSA

Overview

This project demonstrates Aspect-Based Sentiment Analysis (ABSA) using PyABSA, a library for aspect-based sentiment analysis. The application allows users to input a sentence, and it extracts aspects, predicts sentiment, and displays the results in a tabular form.

Getting Started

Prerequisites

• Python 3.x
• Install required dependencies: streamlit, pyabsa, pandas

pip install -r requirements

Running the Application

1. Clone the repository

git clone https://github.com/shaadclt/Aspect-Based-Sentiment-Analysis.git
cd Aspect-Based-Sentiment-Analysis

2. Run the streamlit app

streamlit run ABSA.py

Usage

1. Enter a sentence in the provided text input.
2. Click the "Analyze" button to perform Aspect-based Sentiment Analysis.
3. View the results in the displayed table.

Result Format

The analysis result is displayed in a table with the following columns.

• Aspect: Aspect number
• Term: Extracted aspect term
• Sentiment: Predicted sentiment (Positive/Negative)
• Confidence (%): Confidence level of the sentiment prediction in percentage.

Contributing

If you'd like to contribute to this project, please follow the standard GitHub Fork & Pull Request workflow.

License

This project is licensed under the MIT License.