TheophileBlard/french-sentiment-analysis-with-bert

How good is BERT ? Comparing BERT to other state-of-the-art approaches on a French sentiment analysis dataset

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Emerging

This project helps you analyze French text to determine if the sentiment expressed is positive or negative. It takes raw French text, such as customer reviews or social media posts, and outputs a clear "Positive" or "Negative" sentiment label. This is ideal for marketers, customer service managers, or anyone needing to quickly understand public opinion or customer feedback in French.

156 stars. No commits in the last 6 months.

Use this if you need highly accurate sentiment analysis for French language text, especially for large volumes of user-generated content.

Not ideal if your primary need is real-time processing of extremely short texts, as the most accurate models are slower, or if you only work with English text.

customer-feedback social-listening market-research brand-reputation French-language-processing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 21 / 25

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Stars

156

Forks

39

Language

Jupyter Notebook

License

MIT

Last pushed

Feb 16, 2023

Commits (30d)

0

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curl "https://pt-edge.onrender.com/api/v1/quality/nlp/TheophileBlard/french-sentiment-analysis-with-bert"

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