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Mining opinion from text documents: A survey

B., Baharudin and K., Khan and A., Khan and E-Malik, Fazal- (2009) Mining opinion from text documents: A survey. In: 2009 3rd IEEE International Conference on Digital Ecosystems and Technologies, DEST '09, 1 June 2009 through 3 June 2009, Istanbul.

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Abstract

Opinion Mining is a process, used for automatic extraction of knowledge from the opinion of others about some particular topic or problem. With the growing availability of online resources on web and popularity of fast and rich resources of opinion sharing such as online review sites and personal blogs, Opinion Mining has become an interesting area of research. World Wide Web is a fastest medium for opinion collection from users. Human perception and user opinion has greater potential for knowledge discovery and decision support. In this paper we have presented a survey which covers techniques and methods that promise to enable us to get opinion oriented information from text. This research effort deals with techniques and challenges related to sentiment analysis and Opinion Mining. We have followed systematic literature review process to conduct this survey. Our focus was mainly on machine learning techniques on the basis of their usage and importance for opinion mining. We have tried to identify most commonly used classification techniques for opinionated documents to assist future research in this area. ©2009 IEEE.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Automatic extraction; Classification technique; Decision supports; Human perception; Knowledge Discovery; On-machines; Online resources; Opinion mining; Research efforts; Sentiment analysis; Systematic literature review; Text classification; Text document; Decision support systems; Information retrieval systems; Learning algorithms; Mining; Research; Surveys; World Wide Web; Text processing
Subjects:Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE:Departments > Computer Information Sciences
ID Code:148
Deposited By: Dr Baharum Baharudin
Deposited On:24 Feb 2010 14:20
Last Modified:19 Jan 2017 08:25

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