Sentiment Analysis of Arabic Tweets: Opinion Target Extraction

被引：1

作者：

Salima, Behdenna ^{[1
]}

Fatiha, Barigou ^{[1
]}

Ghalem, Belalem ^{[1
]}

机构：

[1] Univ Oran 1, Comp Sci Dept, Fac Sci, PB 1524 El MNaouer, Oran, Algeria

来源：

MODELLING AND IMPLEMENTATION OF COMPLEX SYSTEMS | 2019年 / 64卷

关键词：

Opinion mining; Arabic sentiment analysis; Opinion target; Machine learning; Arabic tweet;

D O I：

10.1007/978-3-030-05481-6_12

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Due to the increased volume of Arabic opinionated posts on different social media, Arabic sentiment analysis is viewed as an important research field. Identifying the target on which opinion has been expressed is the aim of this work. Opinion target extraction is a problem that was generally very little treated in Arabic text. In this paper, an opinion target extraction method from Arabic tweets is proposed. First, as a preprocessing phase, several feature forms from tweets are extracted to be examined. The aim of these forms is to evaluate their impacts on accuracy. Then, two classifiers, SVM and Naive Bayes are trained. The experiment results show that, with 500 tweets collected and manually tagged, SVM gives the highest precision and recall (86%).

引用

页码：158 / 167

页数：10

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