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Sentiment Analysis of Arabic Documents: Main Challenges and Recent Advances
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Author(s): Hichem Rahab (ICISI Laboratory, University of Khenchela, Algeria), Mahieddine Djoudi (TechNE Laboratory, University of Poitiers, France)and Abdelhafid Zitouni (LIRE Laboratory, University of Constantine 2, Algeria)
Copyright: 2021
Pages: 25
Source title:
Natural Language Processing for Global and Local Business
Source Author(s)/Editor(s): Fatih Pinarbasi (Istanbul Medipol University, Turkey)and M. Nurdan Taskiran (Istanbul Medipol University, Turkey)
DOI: 10.4018/978-1-7998-4240-8.ch013
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Abstract
Today, it is usual that a consumer seeks for others' feelings about their purchasing experience on the web before a simple decision of buying a product or a service. Sentiment analysis intends to help people in taking profit from the available opinionated texts on the web for their decision making, and business is one of its challenging areas. Considerable work of sentiment analysis has been achieved in English and other Indo-European languages. Despite the important number of Arabic speakers and internet users, studies in Arabic sentiment analysis are still insufficient. The current chapter vocation is to give the main challenges of Arabic sentiment together with their recent proposed solutions in the literature. The chapter flowchart is presented in a novel manner that obtains the main challenges from presented literature works. Then it gives the proposed solutions for each challenge. The chapter reaches the finding that the future tendency will be toward rule-based techniques and deep learning, allowing for more dealings with Arabic language inherent characteristics.
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