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...
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| Veröffentlicht in: | Language and linguistics compass Jg. 10; H. 12; S. 701 - 719 |
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| 1. Verfasser: | |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Oxford
Blackwell Publishing Ltd
01.12.2016
Wiley Subscription Services, Inc |
| Schlagworte: | |
| ISSN: | 1749-818X, 1749-818X |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | 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. |
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| Bibliographie: | 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 |