readme: ---
  language: "en"
  tags:
  - roberta
  - sentiment
  - twitter
  
  widget:
  - text: "This looks tasty. Where can I buy it??"
  - text: "Now I want this, too."
  - text: "You look great today!"
  - text: "I just love spring and sunshine!"
  
  ---
  
  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
  
  ```python
  from transformers import pipeline
  classifier = pipeline("text-classification", model="j-hartmann/purchase-intention-english-roberta-large", return_all_scores=True)
  classifier("I want this!")
  ```
  
  ```python
  Output:
  [[{'label': 'no', 'score': 0.0014553926885128021},
    {'label': 'yes', 'score': 0.9985445737838745}]]
  ```
  
  # Reference
  Please cite [this paper](https://journals.sagepub.com/doi/full/10.1177/00222437211037258) when you use our model. Feel free to reach out to [jochen.hartmann@tum.de](mailto: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}
  }
  ```