With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

The rapid growth of the internet has reached the fourth generation, ie, web 4.0, which
supports Sentiment Analysis (SA) in many applications such as social media, marketing, risk …

Multimodal sentiment analysis is a develo** area of research, which involves the
identification of sentiments in videos. Current research considers utterances as independent …

Opinion mining is considered as a subfield of natural language processing, information
retrieval and text mining. Opinion mining is the process of extracting human thoughts and …

Multimodal sentiment analysis is a very actively growing field of research. A promising area
of opportunity in this field is to improve the multimodal fusion mechanism. We present a …

With the increasing popularity of video sharing websites such as YouTube and Facebook,
multimodal sentiment analysis has received increasing attention from the scientific …

Emotion recognition is challenging due to the emotional gap between emotions and audio-
visual features. Motivated by the powerful feature learning ability of deep neural networks …

Detecting sentiments in natural language is tricky even for humans, making its automated
detection more complicated. This research proffers a hybrid deep learning model for fine …

Compared with survey polls, social media can yield a better and more comprehensive
understanding of public perceptions of special topics in a more scientific manner. However …

Traditional text emotion analysis methods are primarily devoted to studying extended texts,
such as news reports and full-length documents. Microblogs are considered short texts that …