Towards Semantic Aspect-Based Sentiment Analysis for Arabic Reviews
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 ho...
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| Veröffentlicht in: | International journal of information systems in the service sector 2020-10, Vol.12 (4), p.1-13 |
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| container_title | International journal of information systems in the service sector |
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| creator | Behdenna, Salima Barigou, Fatiha Belalem, Ghalem |
| description | 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. |
| doi_str_mv | 10.4018/IJISSS.2020100101 |
| format | Article |
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| identifier | ISSN: 1935-5688 |
| ispartof | International journal of information systems in the service sector, 2020-10, Vol.12 (4), p.1-13 |
| issn | 1935-5688 1935-5696 |
| language | eng |
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| source | ProQuest Central UK/Ireland; ProQuest Central |
| subjects | Analysis Arabic language Computer science Data mining Datasets Dictionaries Documents Information systems Linguistics Machine learning Ontology Semantics Sentences Sentiment analysis Social networks |
| title | Towards Semantic Aspect-Based Sentiment Analysis for Arabic Reviews |
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