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--- |
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title: sentiment-analysis-committee |
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emoji: 👥 |
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colorFrom: blue |
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colorTo: green |
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sdk: gradio |
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sdk_version: "4.12.0" |
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app_file: app.py |
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pinned: false |
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--- |
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# Sentiment Analysis Committee |
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A comprehensive sentiment analysis tool using multiple methods, including BERT (Base and Large), DistilBERT, SiEBERT, TextBlob, VADER, and AFINN. |
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## How to Use |
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Enter text into the interface to receive sentiment analyses from various methods. The committee's decision is based on the majority of votes among the methods. |
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## Technical Details |
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This project leverages various natural language processing models to evaluate the sentiment of entered text: |
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- **BERT Base and BERT Large**: Transformer-based models providing sentiment scores and labels. BERT Large is a larger variant of BERT with more layers, potentially offering more nuanced sentiment analysis. |
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- **DistilBERT**: A distilled version of BERT, optimized for speed and efficiency. |
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- **SiEBERT**: A RoBERTa-based model fine-tuned for sentiment analysis. |
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- **TextBlob**: Utilizes Naive Bayes classifiers, offering straightforward sentiment evaluations. |
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- **VADER**: Designed for social media and short texts, giving a compound sentiment score. |
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- **AFINN**: A lexical method assigning scores to words, indicating sentiment intensity. |
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The final decision of the committee is determined by a majority vote approach, providing a balanced sentiment analysis. |
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## Additional Information |
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- Developed by Ramon Mayor Martins (2023) |
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- E-mail: [rmayormartins@gmail.com](mailto:rmayormartins@gmail.com) |
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- Homepage: [https://rmayormartins.github.io/](https://rmayormartins.github.io/) |
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- Twitter: [@rmayormartins](https://twitter.com/rmayormartins) |
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- GitHub: [https://github.com/rmayormartins](https://github.com/rmayormartins) |
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## Notes |
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- The committee's decision is democratic, based on the majority vote from the utilized methods. |
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- The project is implemented in Python and hosted on Hugging Face Spaces. |
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