AnujSinghML/Aspect-Based-Sentiment-Analysis-ABSA-

This repository shows the implementation of a BERT based model which is trained to do aspect based sentiment analysis. The predictor- toolkit uses the best trained model to predict sentiment of user provided inputs.

15
/ 100
Experimental

This tool helps marketing analysts, product managers, and customer feedback specialists understand specific opinions expressed in customer reviews or social media. You provide text (like a restaurant review) and an aspect (like "service" or "food"), and it tells you the sentiment (positive, negative, or neutral) towards that particular aspect. It's designed for anyone needing detailed sentiment insights beyond general positive/negative classifications.

No commits in the last 6 months.

Use this if you need to pinpoint specific sentiments about different features or categories within a single piece of text, such as determining if a customer liked the 'ambiance' but disliked the 'pricing' in the same review.

Not ideal if you only need a broad positive/negative sentiment for entire documents or if you don't have clearly definable aspects to analyze.

customer-feedback market-research product-analysis reputation-management social-listening
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 0 / 25

How are scores calculated?

Stars

12

Forks

Language

Python

License

Last pushed

Apr 17, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/AnujSinghML/Aspect-Based-Sentiment-Analysis-ABSA-"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.