Due to the vast volumes of newly streamed data on the Internet and social media, the use of
sentiment analysis (SA) to extract information and analyze people's opinions has become a …

Sentiment analysis is the process of using natural language processing, computational
linguistics, and other text analysis techniques to identify and extract subjective information in …

Multimodal data can convey user emotions and feelings more effectively and interactively
than unimodal content. Thus, multimodal sentiment analysis (MSA) research has recently …

The recent advancement in internet 2.0 creates a scope to connect people worldwide using
society 2.0 and web 2.0 technologies. This new era allows the consumer to directly connect …

Social networks such as twitter have emerged as social platforms that can impart a massive
knowledge base for people to share their unique ideas and perspectives on various topics …

The issue of the Global Recession is hitting various countries, including Indonesia. Many
Indonesians have expressed their opinions on the issue of the global recession in 2023, one …

Class imbalance problem (CIP) in a dataset is a major challenge that significantly affects the
performance of Machine Learning (ML) models resulting in biased predictions. Numerous …

In this paper, we explore the effectiveness of the GPT-3 model in tackling imbalanced
sentiment analysis, focusing on the Coursera online course review dataset that exhibits high …

Twitter has become a unique platform for social interaction from people all around the world,
leading to an extensive amount of knowledge that can be used for various reasons. People …

Multimodal Sentiment Analysis (SA) is gaining popularity due to its broad application
potential. The existing studies have focused on the SA of single modalities, such as texts or …