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.
Intended Uses
FinTwitBERT-sentiment is intended for classifying financial tweets or other financial social media texts.
Dataset
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.
1from transformers import pipeline
23# Create a sentiment analysis pipeline4pipe = pipeline(5"sentiment-analysis",6 model="StephanAkkerman/FinTwitBERT-sentiment",7)89# Get the predicted sentiment10print(pipe("Nice 9% pre market move for $para, pump my calls Uncle Buffett 🤑"))
Citing & Authors
If you use FinTwitBERT or FinTwitBERT-sentiment in your research, please cite us as follows, noting that both authors contributed equally to this work:
@misc{FinTwitBERT,
author = {Stephan Akkerman, Tim Koornstra},
title = {FinTwitBERT: A Specialized Language Model for Financial Tweets},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/TimKoornstra/FinTwitBERT}}
}
Additionally, if you utilize the sentiment classifier, please cite:
@misc{FinTwitBERT-sentiment,
author = {Stephan Akkerman, Tim Koornstra},
title = {FinTwitBERT-sentiment: A Sentiment Classifier for Financial Tweets},
year = {2023},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/StephanAkkerman/FinTwitBERT-sentiment}}
}
License
This project is licensed under the MIT License. See the LICENSE file for details.
