Computational approaches to subjectivity and sentiment analysis: Present and envisaged methods and applications

被引：50

作者：

Balahur, Alexandra ^{[1
]}

Mihalcea, Rada ^{[2
]}

Montoyo, Andres ^{[3
]}

机构：

[1] European Commiss Joint Res Ctr, I-21027 Ispra, VA, Italy

[2] Univ Michigan, Dept Comp Sci & Engn, Ann Arbor, MI 48109 USA

[3] Univ Alicante, Dept Software & Comp Syst, E-03080 Alicante, Spain

来源：

COMPUTER SPEECH AND LANGUAGE | 2014年 / 28卷 / 01期

关键词：

Subjectivity analysis; Sentiment analysis; Multilingual resources; Social Media mining; Chat analysis;

D O I：

10.1016/j.csl.2013.09.003

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Recent years have witnessed a surge of interest in computational methods for affect, ranging from opinion mining, to subjectivity detection, to sentiment and emotion analysis. This article presents a brief overview of the latest trends in the field and describes the manner in which the articles contained in the special issue contribute to the advancement of the area. Finally, we comment on the current challenges and envisaged developments of the subjectivity and sentiment analysis fields, as well as their application to other Natural Language Processing tasks and related domains. (C) 2013 Published by Elsevier Ltd.

引用

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页数：6

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