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 …

Sentiment analysis is a method within natural language processing that evaluates and
identifies the emotional tone or mood conveyed in textual data. Scrutinizing words and …

Sentiment analysis is an emerging technology that aims to explore people's attitudes toward
an entity. It can be applied in a variety of different fields and scenarios, such as product …

In recent years, affective computing has become a topic of considerable interest, driven by
its ability to enhance several domains, such as mental health monitoring, human–computer …

Social media is a powerful source of communication among people to share their sentiments
in the form of opinions and views about any topic or article, which results in an enormous …

Emotion recognition in conversations is a challenging task that has recently gained
popularity due to its potential applications. Until now, however, a large-scale multimodal …

Previous studies in multimodal sentiment analysis have used limited datasets, which only
contain unified multimodal annotations. However, the unified annotations do not always …

Analyzing human multimodal language is an emerging area of research in NLP. Intrinsically
this language is multimodal (heterogeneous), sequential and asynchronous; it consists of …

Multimodal research is an emerging field of artificial intelligence, and one of the main
research problems in this field is multimodal fusion. The fusion of multimodal data is the …

With the proliferation of user-generated online videos, Multimodal Sentiment Analysis (MSA)
has attracted increasing attention recently. Despite significant progress, there are still two …