Negation-aware Framework for Sentiment Analysis in Arabic Reviews

被引：10

作者：

Duwairi, Rehab M. ^{[1
]}

Alshboul, Mohammad A. ^{[2
]}

机构：

[1] Jordan Univ Sci & Technol, Dept Comp Informat Syst, Irbid 22110, Jordan

[2] Jordan Univ Sci & Technol, Dept Comp Engn, Irbid 22110, Jordan

来源：

2015 3RD INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD (FICLOUD) AND INTERNATIONAL CONFERENCE ON OPEN AND BIG (OBD) | 2015年

关键词：

Sentiment analysis; sentiment detection; opinion mining; language morphology; valence shifters;

D O I：

10.1109/FiCloud.2015.115

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Sentiment analysis deals with identifying polarity orientation embedded in users' comments and reviews. It aims at discriminating positive reviews from negative ones. Sentiment is related to culture and language morphology. In this paper, we investigate the effects of language morphology on sentiment analysis in reviews written in the Arabic language. In particular, we investigate, in details, how negation affects sentiments. We also define a set of rules that capture the morphology of negations in Arabic. These rules are then used to detect sentiment taking care of negated words. Experimentations prove that our suggested approach is superior to several existing methods that deal with sentiment detection in Arabic reviews.

引用

页码：731 / 735

页数：5

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