Multimodal Sentiment Classification (MSC) uses multimodal data, such as images and texts,
to identify the users' sentiment polarities from the information posted by users on the Internet …

This paper proposes a novel hybrid model for sentiment analysis. The model leverages the
strengths of both the Transformer model, represented by the Robustly Optimized BERT …

The advent of the Social Web has enabled anyone with an Internet connection to easily
create and share their ideas, opinions and content with millions of other people around the …

Multimodality sentiment analysis in the social Internet of Things is a developing field, which
is basic to empathetic mechanisms, affective computing, and artificial intelligence. Current …

Multimodal sentiment analysis (MSA) is a very challenging task due to its complex and
complementary interactions between multiple modalities, which can be widely applied into …

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 …

With the rapid development of social networks, more and more people express their
emotions and opinions via online videos. However, most of the current research on …

With the fastest growth of information and communication technology (ICT), the availability of
web content on social media platforms is increasing day by day. Sentiment analysis from …

More and more users are getting used to posting images and text on social networks to
share their emotions or opinions. Accordingly, multimodal sentiment analysis has become a …

An integrated deep learning paradigm for the analysis of document-based sentiments is
presented in this article. Generally, sentiment analysis has enormous applications in the real …