tatimohammed/Darija-Sentiment-Analysis

In the context of Morocco (Darija), sentiment analysis can be an invaluable asset for businesses and organizations looking to better understand the satisfaction of their customers. We will fine-tune a model for Darija

20
/ 100
Experimental

This tool helps businesses and organizations understand customer satisfaction by analyzing text written in Darija, the Moroccan dialect of Arabic. It takes social media posts, reviews, or other customer feedback in Darija and identifies the sentiment as positive or negative, providing insights into customer opinions. It's designed for anyone who needs to gauge public or customer sentiment specifically within a Moroccan context.

No commits in the last 6 months.

Use this if you need to quickly and accurately determine the sentiment (positive or negative) of text data written in Darija to understand customer feedback or public opinion.

Not ideal if your text data is in a language other than Darija or if you require more nuanced sentiment categories beyond just positive/negative.

customer-satisfaction social-listening market-research public-opinion brand-reputation
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 7 / 25

How are scores calculated?

Stars

11

Forks

1

Language

Jupyter Notebook

License

Last pushed

May 07, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/tatimohammed/Darija-Sentiment-Analysis"

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