阿拉伯语情感分析方法综述

Youssra Zahidi, Yacine El Younoussi, Yassine Al-Amrani
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引用次数: 0

摘要

在过去的几年里,阿拉伯语情感分析(ASA)已经成为机器学习(ML)和自然语言处理(NLP)领域最重要的市场和科学研究趋势话题。它试图识别在不同领域的一个文本的意见取向(积极,中立或消极),它已经取得了显著的成果,特别是在教育领域,换句话说,ASA是用来改善教育,试图了解学生的学习程度和监测学生的表现。由于阿拉伯语在正字法、词法和方言方面的复杂性。阿拉伯语的情感分析非常困难,与英语等其他语言相比,它被认为是一个更具挑战性的过程。在这项工作中,我们试图对阿拉伯情感方法以及各种强大的现有技术进行比较分析。
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Arabic Sentiment Analysis Approaches: An Overview
In the last few years, Arabic Sentiment Analysis (ASA) has become the most important trends topic of market and scientific research in Machine Learning (ML) and Natural Language Processing (NLP) fields. It tries to identify the opinion orientation (positivity, neutrality or negativity) of a piece text in different domains and it has gained significant results especially in the field of education, in other words ASA is utilized to ameliorate education by trying to understand the learning degree of students and monitoring the performance of students. Due to Arabic complexities at the level of orthography, morphology and dialects. Sentiment analysis for Arabic language is very difficult and it considered as a more challenging process compared to other languages like English. In this work, we tried to give a comparative analysis of Arabic Sentiment approaches, together with various powerful existing techniques.
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