The rapid growth of Internet-based applications, such as social media platforms and blogs,
has resulted in comments and reviews concerning day-to-day activities. Sentiment analysis …

Sentiment analysis has proven to be a valuable tool to gauge public opinion in different
disciplines. It has been successfully employed in financial market prediction, health issues …

Ensemble learning techniques have achieved state-of-the-art performance in diverse
machine learning applications by combining the predictions from two or more base models …

Sentiment analysis, one of the research hotspots in the natural language processing field,
has attracted the attention of researchers, and research papers on the field are increasingly …

Sentiment analysis has come long way since it was introduced as a natural language
processing task nearly 20 years ago. Sentiment analysis aims to extract the underlying …

Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …

The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …

This study presents a thorough examination of various Generative Pretrained Transformer
(GPT) methodologies in sentiment analysis, specifically in the context of Task 4 on the …

This review presents a comprehensive exploration of hybrid and ensemble deep learning
models within Natural Language Processing (NLP), shedding light on their transformative …

Aspect-level sentiment analysis (ALSA) is the process of collecting, processing, analyzing,
inferring, and synthesizing subjective sentiments of entities contained in texts at the aspect …