Deep learning for sentiment analysis

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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Language and linguistics compass Ročník 10; číslo 12; s. 701 - 719
Hlavní autor: Rojas-Barahona, Lina Maria
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Blackwell Publishing Ltd 01.12.2016
Wiley Subscription Services, Inc
Témata:
ISSN:1749-818X, 1749-818X
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
Bibliografie:Industry
ark:/67375/WNG-VCVKFDXB-W
ArticleID:LNC312228
French Services
Competitivity General Direction
istex:F303D943413C1F7CE374A8153B4082B899B596B9
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1749-818X
1749-818X
DOI:10.1111/lnc3.12228