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README.md
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# Predictions on a data set
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If you want to predict sentiment for your own data, we provide an example script via [Google Colab](https://colab.research.google.com/notebooks/intro.ipynb). You can load your data to a Google Drive and run the script for free on a Colab GPU. Set-up only takes a few minutes. We suggest that you manually label a subset of your data to evaluate performance for your use case. For performance benchmark values across various sentiment analysis contexts, please refer to our paper ([Hartmann et al. 2022](https://
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/chrsiebert/sentiment-roberta-large-english/blob/main/sentiment_roberta_prediction_example.ipynb)
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Other values were left at their defaults as listed [here](https://huggingface.co/transformers/main_classes/trainer.html#transformers.TrainingArguments).
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# Citation and contact
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Please cite [this paper](https://
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```
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@article{hartmann2022,
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title={More than a feeling: Accuracy and Application of Sentiment Analysis},
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author={Hartmann, Jochen and Heitmann, Mark and Siebert, Christian and Schamp, Christina},
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journal={International Journal of Research in Marketing
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year={2022}
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}
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```
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# Predictions on a data set
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If you want to predict sentiment for your own data, we provide an example script via [Google Colab](https://colab.research.google.com/notebooks/intro.ipynb). You can load your data to a Google Drive and run the script for free on a Colab GPU. Set-up only takes a few minutes. We suggest that you manually label a subset of your data to evaluate performance for your use case. For performance benchmark values across various sentiment analysis contexts, please refer to our paper ([Hartmann et al. 2022](https://www.sciencedirect.com/science/article/pii/S0167811622000477?via%3Dihub)).
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/chrsiebert/sentiment-roberta-large-english/blob/main/sentiment_roberta_prediction_example.ipynb)
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Other values were left at their defaults as listed [here](https://huggingface.co/transformers/main_classes/trainer.html#transformers.TrainingArguments).
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# Citation and contact
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Please cite [this paper](https://www.sciencedirect.com/science/article/pii/S0167811622000477?via%3Dihub) (Forthcoming in the [IJRM](https://www.journals.elsevier.com/international-journal-of-research-in-marketing)) when you use our model. Feel free to reach out to [christian.siebert@uni-hamburg.de](mailto:christian.siebert@uni-hamburg.de) with any questions or feedback you may have.
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```
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@article{hartmann2022,
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title={More than a feeling: Accuracy and Application of Sentiment Analysis},
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author={Hartmann, Jochen and Heitmann, Mark and Siebert, Christian and Schamp, Christina},
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journal={International Journal of Research in Marketing},
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year={2022}
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}
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```
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