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--- |
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language: |
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- en |
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tags: |
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- text-classification |
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- sentiment-analysis |
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- sentiment-classification |
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- targeted-sentiment-classification |
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- target-depentent-sentiment-classification |
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license: "apache-2.0" |
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datasets: "fhamborg/news_sentiment_newsmtsc" |
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--- |
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# NewsSentiment: easy-to-use, high-quality target-dependent sentiment classification for news articles |
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## Important: [use our PyPI package](https://pypi.org/project/NewsSentiment/) instead of this model on the Hub |
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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/). |
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## Description |
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This model is the currently [best performing](https://aclanthology.org/2021.eacl-main.142.pdf) |
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targeted sentiment classifier for news articles. In contrast to regular sentiment |
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classification, targeted sentiment classification allows you to provide a target in a sentence. |
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Only for this target, the sentiment is then predicted. This is more reliable in many |
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cases, as demonstrated by the following simplistic example: "I like Bert, but I hate Robert." |
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This model is also available as an easy-to-use PyPI package named [`NewsSentiment`](https://pypi.org/project/NewsSentiment/) and |
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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 |
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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 |
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dataset, the model, and its source code can be viewed in our [GitHub repository](https://github.com/fhamborg/NewsMTSC). |
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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. |
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# How to cite |
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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)): |
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``` |
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@InProceedings{Hamborg2021b, |
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author = {Hamborg, Felix and Donnay, Karsten}, |
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title = {NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles}, |
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booktitle = {Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)}, |
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year = {2021}, |
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month = {Apr.}, |
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location = {Virtual Event}, |
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} |
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``` |
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