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Towards Semantic Aspect-Based Sentiment Analysis for Arabic Reviews
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Author(s): Salima Behdenna (Department of Computer Science, Faculty of Exact and Applied Sciences, Laboratoire d'Informatique d'Oran (LIO), Université Oran1 Ahmed Ben Bella, Oran, Algeria), Fatiha Barigou (Department of Computer Science, Faculty of Exact and Applied Sciences, Laboratoire d'Informatique d'Oran (LIO), Université Oran1 Ahmed Ben Bella, Oran, Algeria)and Ghalem Belalem (Department of Computer Science, Faculty of Exact and Applied Sciences, Laboratoire d'Informatique d'Oran (LIO), Université Oran1 Ahmed Ben Bella, Oran, Algeria)
Copyright: 2022
Pages: 14
Source title:
Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6303-1.ch077
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Abstract
Sentiment analysis is a text mining discipline that aims to identify and extract subjective information. This growing field results in the emergence of three levels of granularity (document, sentence, and aspect). However, both the document and sentence levels do not find what exactly the opinion holder likes and dislikes. Furthermore, most research in this field deals with English texts, and very limited researches are undertaken on Arabic language. In this paper, the authors propose a semantic aspect-based sentiment analysis approach for Arabic reviews. This approach utilizes the semantic of description logics and linguistic rules in the identification of opinion targets and their polarity.
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