Mining opinion from text documents: A survey

• Main Authors: B., Baharudin, K., Khan, A., Khan, E-Malik, Fazal-
• Format: Conference or Workshop Item
• Published: 2009
• Subjects: Q Science (General); QA75 Electronic computers. Computer science
• Online Access: http://eprints.utp.edu.my/148/1/paper.pdf; http://www.scopus.com/inward/record.url?eid=2-s2.0-71649100340&partnerID=40&md5=4381ae0ec8279360be0d0a90bd8b92cd; http://eprints.utp.edu.my/148/
• Institution: Universiti Teknologi Petronas

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.