Challenges and future in deep learning for sentiment analysis: a comprehensive review and a proposed novel hybrid approach
Social media is used to categorise products or services, but analysing vast comments is time-
consuming. Researchers use sentiment analysis via natural language processing …
consuming. Researchers use sentiment analysis via natural language processing …
Improving sentiment classification using a RoBERTa-based hybrid model
Introduction Several attempts have been made to enhance text-based sentiment analysis's
performance. The classifiers and word embedding models have been among the most …
performance. The classifiers and word embedding models have been among the most …
Query-induced multi-task decomposition and enhanced learning for aspect-based sentiment quadruple prediction
H Zhang, X Song, X Jia, C Yang, Z Chen… - … Applications of Artificial …, 2024 - Elsevier
A complete sentiment analysis of product and service reviews has attracted growing
concerns from merchants to enhance personalized marketing activities. Aspect sentiment …
concerns from merchants to enhance personalized marketing activities. Aspect sentiment …
Improving emotion classification in e-commerce customer review analysis using GPT and meta‑ensemble deep learning technique for multilingual system
N Hicham, H Nassera - Multimedia Tools and Applications, 2024 - Springer
In recent years, the field of natural language processing has placed a significant emphasis
on multilingual emotion classification, particularly within social media analysis. This study …
on multilingual emotion classification, particularly within social media analysis. This study …
Enhancing Imbalanced Sentiment Analysis: A GPT-3-Based Sentence-by-Sentence Generation Approach
C Suhaeni, HS Yong - Applied Sciences, 2024 - mdpi.com
This study addresses the challenge of class imbalance in sentiment analysis by utilizing
synthetic data to balance training datasets. We introduce an innovative approach using the …
synthetic data to balance training datasets. We introduce an innovative approach using the …
Enhancing Spam Detection with GANs and BERT Embeddings: A Novel Approach to Imbalanced Datasets
A Filali, M Merras - Procedia Computer Science, 2024 - Elsevier
In recent years, the prevalence of imbalanced datasets has posed significant challenges to
traditional machine learning models. This imbalance is especially pronounced in fields such …
traditional machine learning models. This imbalance is especially pronounced in fields such …
Twitter Sentiment Analysis of COVID-19 Vaccination Integrating SenticNet-7 and SentiWordNet-Adjusted VADER Models
PC Sridevi, T Velmurugan - International Journal of Computer …, 2024 - cspub-ijcisim.org
Social media platforms in the modern era are enormous informational databases that
continually generate massive volumes of data that provide deep insights into human …
continually generate massive volumes of data that provide deep insights into human …
Sentiment Analysis About Legislative Elections using Deep Learning with LSTM and CNN Models
NA Angraini, KM Lhaksmana - Building of Informatics …, 2024 - ejurnal.seminar-id.com
The election of legislative members is a significant moment from the perspective of
democracy, influencing the policies and direction of a country. In the digital era, sentiment …
democracy, influencing the policies and direction of a country. In the digital era, sentiment …
Enhancing Restaurant Customer Review Analysis: Multi-Class Text Classification with BERT
Online customer reviews can be valuable information when processed with the right
techniques. Businesses aim to enhance their strategies in managing operations by …
techniques. Businesses aim to enhance their strategies in managing operations by …
Attention-Based Ensemble for Mitigating Side Effects of Data Imbalance Method
YH Park, YS Choi, W Liermann… - Annual Conference on …, 2023 - koreascience.kr
일반적으로 딥러닝 모델은 모든 라벨에 데이터 수가 균형을 이룰 때 가장 좋은 성능을 보인다.
그러나 현실에서는 특정라벨에 대한 데이터가 부족한 경우가 많으며 이로 인해 불균형 데이터 …
그러나 현실에서는 특정라벨에 대한 데이터가 부족한 경우가 많으며 이로 인해 불균형 데이터 …