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--- |
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language: "en" |
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tags: |
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- roberta |
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- sentiment |
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- twitter |
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widget: |
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- text: "This looks tasty. Where can I buy it??" |
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- text: "Now I want this, too." |
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- text: "You look great today!" |
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- text: "I just love spring and sunshine!" |
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--- |
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This RoBERTa-based model can classify *expressed purchase intentions* in English language text in 2 classes: |
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- purchase intention 🤩 |
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- no purchase intention 😐 |
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The model was fine-tuned on 2,000 manually annotated social media posts. |
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The hold-out accuracy is 95% (vs. a balanced 50% random-chance baseline). |
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For details on the training approach see Web Appendix F in Hartmann et al. (2021). |
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# Application |
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```python |
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from transformers import pipeline |
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classifier = pipeline("text-classification", model="j-hartmann/purchase-intention-english-roberta-large", return_all_scores=True) |
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classifier("I want this!") |
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``` |
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```python |
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Output: |
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[[{'label': 'no', 'score': 0.0014553926885128021}, |
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{'label': 'yes', 'score': 0.9985445737838745}]] |
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``` |
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# Reference |
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Please cite [this paper](https://journals.sagepub.com/doi/full/10.1177/00222437211037258) when you use our model. Feel free to reach out to [j.p.hartmann@rug.nl](mailto:j.p.hartmann@rug.nl) with any questions or feedback you may have. |
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``` |
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@article{hartmann2021, |
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title={The Power of Brand Selfies}, |
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author={Hartmann, Jochen and Heitmann, Mark and Schamp, Christina and Netzer, Oded}, |
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journal={Journal of Marketing Research} |
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year={2021} |
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} |
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``` |
