Nix07/Utilizing-BERT-for-Aspect-Based-Sentiment-Analysis

Targeted Aspect-based Sentiment Analysis on SentiHood Dataset (PyTorch)

29
/ 100
Experimental

This project helps businesses and researchers analyze public opinion by pinpointing specific features or topics in text (like a product's 'battery life' or a restaurant's 'service') and determining the sentiment towards them. You provide raw text data, and it outputs a detailed breakdown of what people like or dislike about different aspects. It's useful for market analysts, product managers, and customer feedback specialists who need granular insights from reviews, social media, or surveys.

No commits in the last 6 months.

Use this if you need to understand not just the overall sentiment of a text, but the sentiment expressed towards particular entities or attributes within that text.

Not ideal if you only need a general positive/negative/neutral sentiment score for entire documents without needing to break it down by specific aspects.

customer-feedback-analysis product-review-mining social-media-listening market-research public-opinion-analysis
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 16 / 25

How are scores calculated?

Stars

11

Forks

6

Language

Jupyter Notebook

License

Last pushed

Aug 04, 2020

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/Nix07/Utilizing-BERT-for-Aspect-Based-Sentiment-Analysis"

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