Simon van Dyk commited on
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Add top text and fix nosible -> NOSIBLE
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README.md
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#
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<p align="center">
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<img src="https://github.com/NosibleAI/nosible-py/blob/main/docs/_static/readme.png?raw=true"/>
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<p>
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## What is it?
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The
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## How to use it
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Using the [HuggingFace datasets library](https://huggingface.co/docs/datasets/):
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* [**Matthew Dicks**](https://www.linkedin.com/in/matthewdicks98/)
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* [**Simon van Dyk**](https://www.linkedin.com/in/simon-van-dyk/)
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# NOSIBLE Financial Sentiment Dataset
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<p align="center">
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<img src="https://github.com/NosibleAI/nosible-py/blob/main/docs/_static/readme.png?raw=true"/>
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## Who is NOSIBLE?
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NOSIBLE is a web-scale vertical search engine. Our worldwide media surveillance products help companies build AI systems that see every worldwide event and act with complete situational awareness. In short, we help companies know everything, all the time. The financial institutions we work with rely on us to deliver media intelligence from every country in every language in real-time. Shortcomings in existing financial datasets and financial models are what inspired us to release this dataset and related models.
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- [NOSIBLE Financial Sentiment v1.1 Base](https://huggingface.co/NOSIBLE/financial-sentiment-v1.1-base)
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- [NOSIBLE Forward Looking v1.1 Base](https://huggingface.co/NOSIBLE/forward-looking-v1.1-base)
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- [NOSIBLE Prediction v1.1 Base](https://huggingface.co/NOSIBLE/prediction-v1.1-base)
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## Why this dataset?
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The NOSIBLE Financial Sentiment Dataset is an open collection of 100,000 cleaned and deduplicated financial news text samples. The data was extracted directly from the NOSIBLE search engine in response to real queries asked by real financial instiutions. Each sample has been labeled as positive, negative, or neutral using a sophisticated labeling pipeline (more information coming soon). The models we trained on the NOSIBLE Financial Sentiment Dataset outperform models trained on the Financial PhraseBank out of sample.
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## What is it?
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The NOSIBLE financial sentiment dataset is a collection of **100k** cleaned and deduplicated financial news samples for financial sentiment classification. Each sample is labeled as **positive**, **negative**, or **neutral**. Financial sentiment is optimised for used in finance as it's sensitive to financial outlook rather than just emotional tone.
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## How to use it
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Using the [HuggingFace datasets library](https://huggingface.co/docs/datasets/):
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* [**Matthew Dicks**](https://www.linkedin.com/in/matthewdicks98/)
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* [**Simon van Dyk**](https://www.linkedin.com/in/simon-van-dyk/)
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* [**Stuart Reid**](https://www.linkedin.com/in/stuartgordonreid/)
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