阿拉伯语情感分类技术综述

Mariam M. Biltawi, W. Etaiwi, Sara Tedmori, A. Hudaib, A. Awajan
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引用次数: 52

摘要

随着在线数据的出现,情感分析近年来受到越来越多的关注。情感分析的目的是确定说话者或作者对特定实体或特定实体的特定特征的整体情感倾向。情感分析的一个基本任务是情感分类,其目的是自动将固执己见的文本分类为积极、消极或中立。虽然关于情感分类的文献相当广泛,但对阿拉伯语中固执己见的文本进行分类的努力却很少。本文对现有的阿拉伯语词汇、机器学习和混合情感分类技术进行了全面的综述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment classification techniques for Arabic language: A survey
With the advent of online data, sentiment analysis has received growing attention in recent years. Sentiment analysis aims to determine the overall sentiment orientation of a speaker or writer towards a specific entity or towards a specific feature of a specific entity. A fundamental task of sentiment analysis is sentiment classification, which aims to automatically classify opinionated text as being positive, negative, or neutral. Although the literature on sentiment classification is quite extensive, only a few endeavors to classify opinionated text written in the Arabic language can be found. This paper provides a comprehensive survey of existing lexicon, machine learning, and hybrid sentiment classification techniques for Arabic language.
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