This RoBERTa-based model can classify expressed purchase intentions in English language text in 2 classes:
- purchase intention 🤩
- no purchase intention 😐
The model was fine-tuned on 2,000 manually annotated social media posts. The hold-out accuracy is 95% (vs. a balanced 50% random-chance baseline). For details on the training approach see Web Appendix F in Hartmann et al. (2021).
Application
from transformers import pipeline
classifier = pipeline("text-classification", model="j-hartmann/purchase-intention-english-roberta-large", return_all_scores=True)
classifier("I want this!")
Output:
[[{'label': 'no', 'score': 0.0014553926885128021},
{'label': 'yes', 'score': 0.9985445737838745}]]
Reference
Please cite this paper when you use our model. Feel free to reach out to jochen.hartmann@tum.de with any questions or feedback you may have.
@article{hartmann2021,
title={The Power of Brand Selfies},
author={Hartmann, Jochen and Heitmann, Mark and Schamp, Christina and Netzer, Oded},
journal={Journal of Marketing Research}
year={2021}
}
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