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

Yusuf ; Kabir Kasum ; Ogbuju ; Emeka ; Abiodun ; Taiwo ; Oladipo ; Francisca

Journal of Computing Theories and Applications 📅 2024 Vol 1, No 3 🔗 DOI: 10.62411/jcta.9999

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

How to Cite

Yusuf, et al. (2024). A Technical Review of the State-of-the-Art Methods in Aspect-Based Sentiment Analysis. Journal of Computing Theories and Applications, 1(3). https://doi.org/10.62411/jcta.9999

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, 2024.

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, 2024.

Yusuf, et al. (2024) 'A Technical Review of the State-of-the-Art Methods in Aspect-Based Sentiment Analysis', Journal of Computing Theories and Applications, 1(3). doi: 10.62411/jcta.9999.

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. 2024;1(3).

An Attention-Enhanced CNN–RBF Framework for Network Intrusion Detection in Imbalanced Traffic

Kabura, Fabrice; Nsabimana, Thierry

A Lightweight Maize Leaf Disease Recognition Using PCA-Compressed MobileNetV2 Features and RBF-SVM

Abubakar, Mustapha; Ibrahim, Yusuf; Ajayi, Ore-Ofe; Saminu, Sani Saleh

Multimodal Deep Learning for Pneumonia Detection Using Wearable Sensors: Toward an Edge-Cloud Framework

Ibam, Emmanuel Onwako; Oluwagbemi, Johnson Bisi

Android Malware Detection Using Machine Learning with SMOTE-Tomek Data Balancing

Masari, Maryam Sufiyanu; Danladi, Maiauduga Abdullahi; Onyinye, Ilori Loretta; Tohomdet, Loreta Katok

Hybrid Real-time Framework for Detecting Adaptive Prompt Injection Attacks in Large Language Models

Prakash, Chandra; Lind, Mary; De La Cruz, Elyson

Integrating Fully Homomorphic Encryption and Zero-Knowledge Proofs for Efficient Verifiable Computation

Qureshi, UmmeAmmara; Doshi, Bhumika; More, Aditya; Joshi, Kashyap; Kumar, Kapil

Tren Sitasi Jurnal