Updated links to published paper

README.md

@@ -14,7 +14,7 @@ This model ("SiEBERT", prefix for "Sentiment in English") is a fine-tuned checkp
 
 
 # Predictions on a data set
-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://papers.ssrn.com/sol3/papers.cfm?abstract_id=3489963)).
+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)).
 
 [![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)
 
@@ -65,13 +65,13 @@ To evaluate the performance of our general-purpose sentiment analysis model, we
 Other values were left at their defaults as listed [here](https://huggingface.co/transformers/main_classes/trainer.html#transformers.TrainingArguments).
   
 # Citation and contact
-Please cite [this paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3489963) (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.
+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.
 
 ```
 @article{hartmann2022,
   title={More than a feeling: Accuracy and Application of Sentiment Analysis},
   author={Hartmann, Jochen and Heitmann, Mark and Siebert, Christian and Schamp, Christina},
-  journal={International Journal of Research in Marketing (Forthcoming)},
+  journal={International Journal of Research in Marketing},
   year={2022}
 }
 ```