Multilingual Epidemiological Text Classification: A Comparative Study (2020.coling-main)
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| Challenge: | a comparative study of multilingual text classification models analyzes the performance of different models based on different languages . low-resource languages are highly influenced by typology of the languages on which the models have been trained or fine-tuned but also by their size. |
| Approach: | They compare machine and deep learning models with a dataset of epidemiological news articles . they find that the performance of the models is proportionate to the training data size . |
| Outcome: | The proposed model outperforms baseline models on a multilingual text classification task . low-resource languages are highly influenced by typology of languages and their size . |
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