Generating Aspect-based Extractive Opinion Summary: Drawing Inferences from Social Media Texts

Authors

  • Rajesh Piryani Department of Computer Science, South Asian University, New Delhi, India
  • Vedika Gupta Department of Computer Science, National Institute of Technology Delhi, Delhi, India
  • Vivek Kumar Singh Department of Computer Science, Banaras Hindu University, Varanasi, India

DOI:

https://doi.org/10.13053/cys-22-1-2784

Keywords:

Aspect-level sentiment analysis, Laptop, Polarity, Sentiment summarization, big data

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.

Downloads

Published

2018-03-30

Issue

Vol. 22 No. 1 (2018): Thematic Issue on Language & Knowledge Engineering (Guest Editors: D. Pinto, D. Vilariño, B. Beltrán)

Section

Articles of the Thematic Issue

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.