Research Repository

Sentiment classification using summaries: A comparative investigation of lexical and statistical approaches

Antai, Roseline (2014) Sentiment classification using summaries: A comparative investigation of lexical and statistical approaches. In: 6th Computer Science and Electronic Engineering Conference (CEEC), 2014, 25-26 Sept. 2014, Colchester.

Full text not available from this repository.

Abstract

Online reviewing has been on the rise and is extremely useful and accessible to web users due to the rise in social networking and more reviewing platforms. Being that some reviews tend to contain more text than is necessary to convey the sentiment of the review, review summarization with respect to polarity classification has become necessary. This work gives a comparative investigation of three forms of summarization approaches used for polarity classification. These include using SentiWordNet for a lexical approach, SVM Light for a statistical approach, and the Open Text Summarizer for a traditional summarization based approach.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 22 Aug 2015 21:20
Last Modified: 22 Aug 2015 21:20
URI: http://repository.essex.ac.uk/id/eprint/14671

Actions (login required)

View Item View Item