| DOI | Resolve DOI: https://doi.org/10.18653/v1/S16-1004 |
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| Author | Search for: Kiritchenko, Svetlana1; Search for: Mohammad, Saif1; Search for: Salameh, Mohammad |
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| Affiliation | - National Research Council of Canada. Information and Communication Technologies
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| Format | Text, Article |
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| Conference | 10th International Workshop on Semantic Evaluation (SemEval-2016), 16-17 June 2016, San Diego, California, USA |
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| Abstract | 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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| Publication date | 2016 |
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| Publisher | Association for Computational Linguistics |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 23001912 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | f75408dc-0a13-42f6-968f-154cd3f7c5d6 |
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| Record created | 2017-05-24 |
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| Record modified | 2020-03-16 |
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