Please use this identifier to cite or link to this item: https://doi.org/10.1109/MIS.2013.30
Title: New avenues in opinion mining and sentiment analysis
Authors: Cambria, E. 
Schuller, B.
Xia, Y.
Havasi, C.
Keywords: AI
intelligent systems
NLP
opinion mining
sentiment analysis
Issue Date: 2013
Citation: Cambria, E., Schuller, B., Xia, Y., Havasi, C. (2013). New avenues in opinion mining and sentiment analysis. IEEE Intelligent Systems 28 (2) : 15-21. ScholarBank@NUS Repository. https://doi.org/10.1109/MIS.2013.30
Abstract: 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.
Source Title: IEEE Intelligent Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/116479
ISSN: 15411672
DOI: 10.1109/MIS.2013.30
Appears in Collections:Staff Publications

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