📅 21 February 2024
DOI: 10.62411/jcta.9999
A Technical Review of the State-of-the-Art Methods in Aspect-Based Sentiment Analysis
Journal of Computing Theories and Applications
Universitas Dian Nuswantoro
📄 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.
🔖 Keywords
#Aspect-based sentiment analysis; Big data; Sentiment analysis; Systematic review; Text mining
ℹ️ Informasi Publikasi
Tanggal Publikasi
21 February 2024
Volume / Nomor / Tahun
Volume 1, Nomor 3, Tahun 2024
📝 HOW TO CITE
Yusuf, Kabir Kasum; Ogbuju, Emeka; Abiodun, Taiwo; Oladipo, Francisca, "A Technical Review of the State-of-the-Art Methods in Aspect-Based Sentiment Analysis," Journal of Computing Theories and Applications, vol. 1, no. 3, Feb. 2024.
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