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Deep learning for sentiment analysis

Accepted version
Peer-reviewed

Type

Article

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Authors

Rojas-Barahona, LM 

Abstract

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.

Description

Keywords

47 Language, Communication and Culture, 4704 Linguistics, Behavioral and Social Science

Journal Title

Linguistics and Language Compass

Conference Name

Journal ISSN

1749-818X
1749-818X

Volume Title

10

Publisher

Wiley
Sponsorship
This work is the result of the research conducted in the context of the ITEA2 1105 Empathic Products project, supported by funding from the French Services, Industry, and Competitivity General Direction.