DOI | Trouver le DOI : https://doi.org/10.3115/v1/N15-1078 |
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Auteur | Rechercher : Salameh, Mohammad; Rechercher : Mohammad, Saif1; Rechercher : Kiritchenko, Svetlana1 |
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Affiliation | - Conseil national de recherches du Canada. Technologies de l'information et des communications
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Format | Texte, Article |
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Conférence | 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, May 31–June 5, 2015, Denver, Colorado, USA |
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Résumé | When text is translated from one language into another, sentiment is preserved to varying degrees. In this paper, we use Arabic social media posts as stand-in for source language text, and determine loss in sentiment predictability when they are translated into English, manually and automatically. As benchmarks, we use manually and automatically determined sentiment labels of the Arabic texts. We show that sentiment analysis of English translations of Arabic texts produces competitive results, w.r.t. Arabic sentiment analysis. We discover that even though translation significantly reduces the human ability to recover sentiment, automatic sentiment systems are still able to capture sentiment information from the translations |
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Date de publication | 2015-05-31 |
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Maison d’édition | Association for Computational Linguistics |
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Dans | |
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Langue | anglais |
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Publications évaluées par des pairs | Oui |
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Numéro NPARC | 23000028 |
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Exporter la notice | Exporter en format RIS |
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Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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Identificateur de l’enregistrement | b9431a3a-e900-4176-9f67-08ad6cd85cae |
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Enregistrement créé | 2016-05-30 |
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Enregistrement modifié | 2020-04-22 |
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