| DOI | Trouver le DOI : https://doi.org/10.18653/v1/S16-1004 |
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| Auteur | Rechercher : Kiritchenko, Svetlana1; Rechercher : Mohammad, Saif1; Rechercher : Salameh, Mohammad |
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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 | 10th International Workshop on Semantic Evaluation (SemEval-2016), 16-17 June 2016, San Diego, California, USA |
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| Résumé | We present a shared task on automatically determining sentiment intensity of a word or a phrase. The words and phrases are taken from three domains: general English, English Twit-ter, and Arabic Twitter. The phrases include those composed of negators, modals, and degree adverbs as well as phrases formed by words with opposing polarities. For each of the three domains, we assembled the datasets that include multi-word phrases and their constituent words, both manually annotated for real-valued sentiment intensity scores. The three datasets were presented as the test sets for three separate tasks (each focusing on a specific domain). Five teams submitted nine system outputs for the three tasks. All datasets created for this shared task are freely available to the research community. |
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| Date de publication | 2016 |
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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 | 23001912 |
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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 | f75408dc-0a13-42f6-968f-154cd3f7c5d6 |
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| Enregistrement créé | 2017-05-24 |
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| Enregistrement modifié | 2020-03-16 |
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