StephanAkkerman
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FinTwitBERT is a language model specifically pre-trained on a large dataset of financial tweets. This specialized BERT model aims to capture the unique jargon and communication style found in the financial Twitter sphere, making it an ideal tool for sentiment analysis, trend prediction, and other financial NLP tasks.
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## Dataset
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FinTwitBERT is pre-trained on several financial tweets datasets, consisting of tweets mentioning stocks and cryptocurrencies:
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- [StephanAkkerman/crypto-stock-tweets](https://huggingface.co/datasets/StephanAkkerman/crypto-stock-tweets): 8,024,269 tweets
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FinTwitBERT is a language model specifically pre-trained on a large dataset of financial tweets. This specialized BERT model aims to capture the unique jargon and communication style found in the financial Twitter sphere, making it an ideal tool for sentiment analysis, trend prediction, and other financial NLP tasks.
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## Sentiment Analysis
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The [FinTwitBERT-sentiment](https://huggingface.co/StephanAkkerman/FinTwitBERT-sentiment) model leverages FinTwitBERT for the sentiment analysis of financial tweets, offering nuanced insights into the prevailing market sentiments.
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## Dataset
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FinTwitBERT is pre-trained on several financial tweets datasets, consisting of tweets mentioning stocks and cryptocurrencies:
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- [StephanAkkerman/crypto-stock-tweets](https://huggingface.co/datasets/StephanAkkerman/crypto-stock-tweets): 8,024,269 tweets
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