SemEval-2016 task 5: aspect based sentiment analysis

Pontiki, Maria; Galanis, Dimitris; Papageorgiou, Haris; Androutsopoulos, Ion; Manandhar, Suresh; Al-Smadi, Mohammad; Al-Ayyoub, Mahmoud; Zhao, Yanyan; Qin, Bing; De Clercq, Orphée; Hoste, Véronique; Apidianaki, Marianna; Tannier, Xavier; Loukachevitch, Natalia; Kotelnikov, Evgeniy; Bel, Nuria; Bel Rafecas, Núria; Jiménez-Zafra, Salud María; Eryiğit, Gülşen

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SemEval-2016 task 5: aspect based sentiment analysis

Document Type: Speech/Conference communication

Version: Published version

Date: 2016

This document is associated with a Creative Common license

ACL materials are Copyright © 1963–2024 ACL; other materials are copyrighted by their respective copyright holders. Materials prior to 2016 here are licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International License. Permission is granted to make copies for the purposes of teaching and research. Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License.

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Citation: Pontiki M, Galanis D, Papageorgiou H, Androutsopoulos I, Manandhar S, Al-Smadi M, et al. SemEval-2016 task 5: aspect based sentiment analysis. In: Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016); 2016 Jun 16-17; San Diego, California. [San Diego]: Association for Computational Linguistics; 2016. p. 19-30. DOI: 10.18653/v1/S16-1002

Permanent link: http://hdl.handle.net/10230/68305

Description:

Comunicació presentada a la 10th International Workshop on Semantic Evaluation (SemEval-2016), celebrada del 16 al 17 de juny de 2016 a San Diego, California.

Abstract:

This paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis (ABSA), a continuation of the respective tasks of 2014 and 2015. In its third year, the task provided 19 training and 20 testing datasets for 8 languages and 7 domains, as well as a common evaluation procedure. From these datasets, 25 were for sentence-level and 14 for text-level ABSA; the latter was introduced for the first time as a subtask in SemEval. The task attracted 245 submissions from 29 teams.