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FinTwitBERT-sentiment

StephanAkkerman

FinTwitBERT-sentiment is a finetuned model for classifying the sentiment of financial tweets. It uses FinTwitBERT as a base model, which has been pre-trained on 10 million financial tweets. This approach ensures that the FinTwitBERT-sentiment has seen enough financial tweets, which have an informal nature, compared to other financial texts, such as news headlines. Therefore this model performs great on informal financial texts, seen on social media. FinTwitBERT-sentiment is intended for classifying financial tweets or other financial social media texts. FinTwitBERT-sentiment has been trained on two datasets. One being a collection of several financial tweet datasets and the other a synthetic dataset created out of the first. - TimKoornstra/financial-tweets-sentiment: 38,091 human-labeled tweets - TimKoornstra/synthetic-financial-tweets-sentiment: 1,428,771 synethtic tweets

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