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# korPolBERT
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This model is a BERT classification model to classify Korean user generated comments into binary labels of liberal or conservative.
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This model was trained on approximately 37,000 user generated comments collected from NAVER\'s news portal.
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license: apache-2.0
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license: apache-2.0
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This model was developed to analyze comment authorship patterns on Korean news articles.
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For further details, refer to our paper on Journalism: [News comment sections and online echo chambers: The ideological alignment between partisan news stories and their user comments](https://journals.sagepub.com/doi/full/10.1177/14648849211069241)
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* This model is a BERT classification model to classify Korean user generated comments into binary labels of liberal or conservative.
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* This model was trained on approximately 37,000 user generated comments collected from NAVER\'s news portal. The dataset was collected in 2019; as such, note that comments related to recent political topics might not be classified correctly.
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* This model is a finetuned model based on ETRI\'s KorBERT.
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### Model performance
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* Accuracy: 0.8322
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* F1-Score: 0.8322
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* For further technical details on the model, refer to our paper for the W-NUT workshop (EMNLP 2019), [The Fallacy of Echo Chambers: Analyzing the Political Slants of User-Generated News Comments in Korean Media](https://aclanthology.org/D19-5548/).
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