Journal of Computing Theories and Applications
Vol. 1 No. 3 (2024): JCTA 1(3) 2024

A Technical Review of the State-of-the-Art Methods in Aspect-Based Sentiment Analysis

Yusuf, Kabir Kasum (Unknown)
Ogbuju, Emeka (Unknown)
Abiodun, Taiwo (Unknown)
Oladipo, Francisca (Unknown)



Article Info

Publish Date
21 Feb 2024

Abstract

With the advent and rapid advancement of text mining technology, a computer-based approach used to capture sentiment standpoints from data in textual form is increasingly becoming a promising field. Detailed information about sentiment can be provided using aspect-based sentiment analysis, which can be used in better decision-making. This study aims to study, observe, and classify previous methods used in aspect-based sentiment analysis. A systematic review is adopted as the method used to collect and review papers to achieve this research's aim. Papers focused on sentiment analysis, aspect extraction, and aspect aggregation from different academic databases such as Scopus, ScienceDirect, IEEE Explore, and Web of Science were gathered based on the inclusion and exclusion criteria of the study. The gathered papers were further reviewed to answer the stated research questions. The findings from the research show the most used methods for aspect extraction, sentiment analysis, and aspect aggregation in aspect-based sentiment analysis. This research offers a robust synthesis of evidence to guide further academic exploration in sentiment analysis.

Copyrights © 2024






Journal Info

Abbrev

jcta

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management

Description

Journal of Computing Theories and Applications (JCTA) is a refereed, international journal that covers all aspects of foundations, theories and the practical applications of computer science. FREE OF CHARGE for submission and publication. All accepted articles will be published online and accessed ...