A review of opinion mining and sentiment classification framework in social networks

Lo, Yee; Potdar, Vidyasagar

doi:10.1109/DEST.2009.5276705

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Access Status

Open access

Authors

Lo, Yee

Potdar, Vidyasagar

Date

2009

Type

Conference Paper

Metadata

Show full item record

Citation

Lo, Yee and Potdar, Vidyasagar. 2009. A review of opinion mining and sentiment classification framework in social networks, in Okyay Kaynak and Mukesh Mohania (ed), International Conference on Digital Ecosystems and Technology (DEST 2009), Jun 1 2009, pp. 396-401. Istanbul, Turkey: IEEE.

Source Title

Proceedings of the international conference on digital ecosystems and technologies (DEST 2009)

Source Conference

International Conference on Digital Ecosystems and Technology (DEST 2009)

DOI

10.1109/DEST.2009.5276705

ISBN

9781424423453

Faculty

Curtin Business School

The Digital Ecosystems and Business Intelligence Institute (DEBII)

School

Centre for Extended Enterprises and Business Intelligence

Remarks

Copyright © 2009 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

URI

http://hdl.handle.net/20.500.11937/7731

Collection

Curtin Research Publications

Abstract

The Web has dramatically changed the way we express opinions on certain products that we have purchased and used, or for services that we have received in the various industries. Opinions and reviews can be easily posted on the Web. such as in merchant sites, review portals, blogs, Internet forums, and much more. These data are commonly referred to as usergenerated content or user-generated media. Both the product manufacturers, as well as potential customers are very interested in this online 'word-of-mouth', as it provides product manufacturers information on their customers likes and dislikes, as well as the positive and negative comments on their products whenever available, giving them better knowledge of their products limitations and advantages over competitors; and also providing potential customers with useful and 'first-hand' information on the products and/or services to aid in their purchase decision making process. This paper discusses the existing works on opinion mining and sentiment classification of customer feedback and reviews online, and evaluates the different techniques used for the process. It focuses on thc areas covered by the evaluated papers, points out the areas that are well covered by many researchers and areas that are neglected in opinion mining and sentiment classification which are open for future research opportunity.