Deep learning for sentiment analysis

被引:77
|
作者
Rojas-Barahona, Lina Maria [1 ]
机构
[1] Univ Cambridge, Dept Engn, Trumpinton St, Cambridge CB2 1PZ, England
来源
LANGUAGE AND LINGUISTICS COMPASS | 2016年 / 10卷 / 12期
关键词
D O I
10.1111/lnc3.12228
中图分类号
H [语言、文字];
学科分类号
05 ;
摘要
Research and industry are becoming more and more interested in finding automatically the polarised opinion of the general public regarding a specific subject. The advent of social networks has opened the possibility of having access to massive blogs, recommendations, and reviews. The challenge is to extract the polarity from these data, which is a task of opinion mining or sentiment analysis. The specific difficulties inherent in this task include issues related to subjective interpretation and linguistic phenomena that affect the polarity of words. Recently, deep learning has become a popular method of addressing this task. However, different approaches have been proposed in the literature. This article provides an overview of deep learning for sentiment analysis in order to place these approaches in context.
引用
收藏
页码:701 / 719
页数:19
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