New Avenues in Opinion Mining and Sentiment Analysis

被引：636

作者：

Cambria, Erik ^{[1
]}

Schuller, Bjoern ^{[2
]}

Xia, Yunqing ^{[3
]}

Havasi, Catherine ^{[4
]}

机构：

[1] Natl Univ Singapore, Temasek Labs, Cognit Sci Programme, Singapore 117548, Singapore

[2] Tech Univ Munich, Inst Human Machine Commun, Machine Intelligence & Signal Proc Grp, D-80290 Munich, Germany

[3] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Beijing, Peoples R China

[4] MIT, Media Lab, Open Mind Common Sense Project, Cambridge, MA 02139 USA

来源：

IEEE INTELLIGENT SYSTEMS | 2013年 / 28卷 / 02期

关键词：

AI; intelligent systems; NLP; opinion mining; sentiment analysis;

D O I：

10.1109/MIS.2013.30

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The distillation of knowledge from the Web—also known as opinion mining and sentiment analysis—is a task that has recently raised growing interest for purposes such as customer service, predicting financial markets, monitoring public security, investigating elections, and measuring a health-related quality of life. This article considers past, present, and future trends of sentiment analysis by delving into the evolution of different tools and techniques—from heuristics to discourse structure, from coarse- to fine-grained analysis, and from keyword- to concept-level opinion mining. © 2001-2011 IEEE.

引用

页码：15 / 21

页数：7

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Cambria, Erik ;

Song, Yangqiu ;

Wang, Haixun ;

Howard, Newton .

IEEE INTELLIGENT SYSTEMS, 2014, 29 (02) :44-51

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