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- W2953884906 abstract "This paper describes the GSI-UPM system for SemEval-2019 Task 5, which tackles multilingual detection of hate speech on Twitter. The main contribution of the paper is the use of a method based on word embeddings and semantic similarity combined with traditional paradigms, such as n-grams, TF-IDF and POS. This combination of several features is fine-tuned through ablation tests, demonstrating the usefulness of different features. While our approach outperforms baseline classifiers on different sub-tasks, the best of our submitted runs reached the 5th position on the Spanish sub-task A." @default.
- W2953884906 created "2019-07-12" @default.
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- W2953884906 date "2019-01-01" @default.
- W2953884906 modified "2023-09-30" @default.
- W2953884906 title "GSI-UPM at SemEval-2019 Task 5: Semantic Similarity and Word Embeddings for Multilingual Detection of Hate Speech Against Immigrants and Women on Twitter" @default.
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- W2953884906 doi "https://doi.org/10.18653/v1/s19-2070" @default.
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