Generating aspect-based extractive opinion summary: Drawing inferences from social media texts

Abstract

This paper presents an integrated framework to generate extractive aspect-based opinion summary from a large volume of free-form text reviews. The framework has three major components: (a) aspect identifier to determine the aspects in a given domain; (b) sentiment polarity detector for computing the sentiment polarity of opinion about an aspect; and (c) summary generator to generate opinion summary. The framework is evaluated on SemEval-2014 dataset and obtains better results than several other approaches. © 2018 Instituto Politecnico Nacional. All rights reserved.