Metaphorical Expressions in Automatic Arabic Sentiment Analysis

Israa Alsiyat, Scott Piao

Abstract
Over the recent years, Arabic language resources and NLP tools have been under rapid development. One of the important tasks for Arabic natural language processing is the sentiment analysis. While a significant improvement has been achieved in this research area, the existing computational models and tools still suffer from the lack of capability of dealing with Arabic metaphorical expressions. Metaphor has an important role in Arabic language due to its unique history and culture. Metaphors provide a linguistic mechanism for expressing ideas and notions that can be different from their surface form. Therefore, in order to efficiently identify true sentiment of Arabic language data, a computational model needs to be able to “read between lines”. In this paper, we examine the issue of metaphors in automatic Arabic sentiment analysis by carrying out an experiment, in which we observe the performance of a state-of-art Arabic sentiment tool on metaphors and analyse the result to gain a deeper insight into the issue. Our experiment evidently shows that metaphors have a significant impact on the performance of current Arabic sentiment tools, and it is an important task to develop Arabic language resources and computational models for Arabic metaphors.
Anthology ID:
2020.lrec-1.604
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
4911–4916
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.604
DOI:
Bibkey:
Cite (ACL):
Israa Alsiyat and Scott Piao. 2020. Metaphorical Expressions in Automatic Arabic Sentiment Analysis. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 4911–4916, Marseille, France. European Language Resources Association.
Cite (Informal):
Metaphorical Expressions in Automatic Arabic Sentiment Analysis (Alsiyat & Piao, LREC 2020)
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PDF:
https://preview.aclanthology.org/nschneid-patch-2/2020.lrec-1.604.pdf
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