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2021 | OriginalPaper | Chapter

A Frequency-Based Approach to Extract Aspect for Aspect-Based Sentiment Analysis

Authors : Rahul Pradhan, Dilip Kumar Sharma

Published in: Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Publisher: Springer Singapore

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Abstract

Data is king nowadays, and users worldwide express their views on different platforms to aggregate this data and analyze it. Sentiment analysis becomes a major tool for analysts. Sentiment analysis can be done on different levels. This will be discussing a more granular level of sentiment analysis using aspect-based sentiment analysis, which aims to predict the sentiment polarity of text for a specific target. The majority of work done in this field focuses on the extraction of aspect or feature and then finding their sentiments polarity and aggregating them to find the whole text's final polarity. Aspect extraction is the key to this process; our work will be focusing on aspect extraction. In this paper, we will address the issue of aspect extraction and then propose our approach to deal with it and show how it is better than these existing approaches.

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Metadata
Title
A Frequency-Based Approach to Extract Aspect for Aspect-Based Sentiment Analysis
Authors
Rahul Pradhan
Dilip Kumar Sharma
Copyright Year
2021
Publisher
Springer Singapore
Book
Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Print ISBN: 978-981-16-0732-5

Electronic ISBN: 978-981-16-0733-2

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-16-0733-2_35