readme: ---
  language: 
  
    - en
  
  tags:
  - text-classification
  - sentiment-analysis
  - sentiment-classification
  - targeted-sentiment-classification
  - target-depentent-sentiment-classification
  
  license: "apache-2.0"
  
  datasets: "fhamborg/news_sentiment_newsmtsc"
  
  ---
  
  # NewsSentiment: easy-to-use, high-quality target-dependent sentiment classification for news articles
  
  ## Important: [use our PyPI package](https://pypi.org/project/NewsSentiment/) instead of this model on the Hub
  The Huggingface Hub architecture currently [does not support](https://github.com/huggingface/transformers/issues/14785) target-dependent sentiment classification since you cannot provide the required inputs, i.e., sentence and target. Thus, we recommend that you use our easy-to-use [PyPI package NewsSentiment](https://pypi.org/project/NewsSentiment/).
  
  ## Description
  
  This model is the currently [best performing](https://aclanthology.org/2021.eacl-main.142.pdf) 
  targeted sentiment classifier for news articles. In contrast to regular sentiment
  classification, targeted sentiment classification allows you to provide a target in a sentence. 
  Only for this target, the sentiment is then predicted. This is more reliable in many
  cases, as demonstrated by the following simplistic example: "I like Bert, but I hate Robert."
  
  This model is also available as an easy-to-use PyPI package named [`NewsSentiment`](https://pypi.org/project/NewsSentiment/) and 
  in its original GitHub repository named [`NewsMTSC`](https://github.com/fhamborg/NewsMTSC), where you will find the dataset the model was trained on, other models for sentiment classification, and a training and testing framework. More information on the model and the dataset (consisting of more than 10k sentences sampled from news articles, each 
  labeled and agreed upon by at least 5 annotators) can be found in our [EACL paper](https://aclanthology.org/2021.eacl-main.142.pdf). The
  dataset, the model, and its source code can be viewed in our [GitHub repository](https://github.com/fhamborg/NewsMTSC).
  
  We recommend to use our [PyPI package](https://pypi.org/project/NewsSentiment/) for sentiment classification since the Huggingface Hub platform seems to [not support](https://github.com/huggingface/transformers/issues/14785) target-dependent sentiment classification.
  
  
  # How to cite
  If you use the dataset or model, please cite our [paper](https://www.aclweb.org/anthology/2021.eacl-main.142/) ([PDF](https://www.aclweb.org/anthology/2021.eacl-main.142.pdf)):
  
  ```
  @InProceedings{Hamborg2021b,
    author    = {Hamborg, Felix and Donnay, Karsten},
    title     = {NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles},
    booktitle = {Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)},
    year      = {2021},
    month     = {Apr.},
    location  = {Virtual Event},
  }
  ```
  